- a - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
-
Coefficients
- a - Variable in class org.apache.commons.math.analysis.interpolation.TricubicSplineFunction
-
Coefficients
- a - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
When all c[i] = 0, a[] becomes normal polynomial coefficients,
i.e.
- a - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Internal weights from Butcher array (without the first empty row).
- a - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
-
Internal weights from Butcher array (without the first empty row).
- a - Variable in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Parameter a of this function.
- a - Variable in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Guessed amplitude.
- a - Variable in class org.apache.commons.math.optimization.fitting.HarmonicFunction
-
Amplitude a.
- a1 - Variable in class org.apache.commons.math.geometry.RotationOrder
-
Axis of the first rotation.
- a2 - Variable in class org.apache.commons.math.geometry.RotationOrder
-
Axis of the second rotation.
- a3 - Variable in class org.apache.commons.math.geometry.RotationOrder
-
Axis of the third rotation.
- A70 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
-
Last row of the Butcher-array internal weights, element 0.
- A72 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
-
Last row of the Butcher-array internal weights, element 2.
- A73 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
-
Last row of the Butcher-array internal weights, element 3.
- A74 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
-
Last row of the Butcher-array internal weights, element 4.
- A75 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
-
Last row of the Butcher-array internal weights, element 5.
- ABS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- abs() - Method in class org.apache.commons.math.complex.Complex
-
Return the absolute value of this complex number.
- abs() - Method in class org.apache.commons.math.fraction.BigFraction
-
- abs() - Method in class org.apache.commons.math.fraction.Fraction
-
Returns the absolute value of this fraction.
- abs(int) - Static method in class org.apache.commons.math.util.FastMath
-
Absolute value.
- abs(long) - Static method in class org.apache.commons.math.util.FastMath
-
Absolute value.
- abs(float) - Static method in class org.apache.commons.math.util.FastMath
-
Absolute value.
- abs(double) - Static method in class org.apache.commons.math.util.FastMath
-
Absolute value.
- abscissas - Variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
-
Abscissas for the current method.
- ABSCISSAS_2 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
-
Abscissas for the 2 points method.
- ABSCISSAS_3 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
-
Abscissas for the 3 points method.
- ABSCISSAS_4 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
-
Abscissas for the 4 points method.
- ABSCISSAS_5 - Static variable in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
-
Abscissas for the 5 points method.
- absoluteAccuracy - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Maximum absolute error.
- absoluteThreshold - Variable in class org.apache.commons.math.optimization.SimpleRealPointChecker
-
Absolute tolerance threshold.
- absoluteThreshold - Variable in class org.apache.commons.math.optimization.SimpleScalarValueChecker
-
Absolute tolerance threshold.
- absoluteThreshold - Variable in class org.apache.commons.math.optimization.SimpleVectorialPointChecker
-
Absolute tolerance threshold.
- absoluteThreshold - Variable in class org.apache.commons.math.optimization.SimpleVectorialValueChecker
-
Absolute tolerance threshold.
- AbstractContinuousDistribution - Class in org.apache.commons.math.distribution
-
Base class for continuous distributions.
- AbstractContinuousDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Default constructor.
- AbstractDistribution - Class in org.apache.commons.math.distribution
-
Base class for probability distributions.
- AbstractDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractDistribution
-
Default constructor.
- AbstractEstimator - Class in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- AbstractEstimator() - Constructor for class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Build an abstract estimator for least squares problems.
- AbstractFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
Basic implementation of
FieldMatrix methods regardless of the underlying storage.
- AbstractFieldMatrix() - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
-
Constructor for use with Serializable
- AbstractFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
-
Creates a matrix with no data
- AbstractFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
-
Create a new FieldMatrix with the supplied row and column dimensions.
- AbstractFormat - Class in org.apache.commons.math.fraction
-
- AbstractFormat() - Constructor for class org.apache.commons.math.fraction.AbstractFormat
-
Create an improper formatting instance with the default number format
for the numerator and denominator.
- AbstractFormat(NumberFormat) - Constructor for class org.apache.commons.math.fraction.AbstractFormat
-
Create an improper formatting instance with a custom number format for
both the numerator and denominator.
- AbstractFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.fraction.AbstractFormat
-
Create an improper formatting instance with a custom number format for
the numerator and a custom number format for the denominator.
- AbstractIntegerDistribution - Class in org.apache.commons.math.distribution
-
Base class for integer-valued discrete distributions.
- AbstractIntegerDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Default constructor.
- AbstractIntegrator - Class in org.apache.commons.math.ode
-
Base class managing common boilerplate for all integrators.
- AbstractIntegrator(String) - Constructor for class org.apache.commons.math.ode.AbstractIntegrator
-
Build an instance.
- AbstractIntegrator() - Constructor for class org.apache.commons.math.ode.AbstractIntegrator
-
Build an instance with a null name.
- AbstractIntegrator.EndTimeChecker - Class in org.apache.commons.math.ode
-
Deprecated.
as of 2.2, this class is not used anymore
- AbstractIntegrator.EndTimeChecker(double) - Constructor for class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
-
Deprecated.
Build an instance.
- AbstractLeastSquaresOptimizer - Class in org.apache.commons.math.optimization.general
-
Base class for implementing least squares optimizers.
- AbstractLeastSquaresOptimizer() - Constructor for class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Simple constructor with default settings.
- AbstractLinearOptimizer - Class in org.apache.commons.math.optimization.linear
-
Base class for implementing linear optimizers.
- AbstractLinearOptimizer() - Constructor for class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Simple constructor with default settings.
- AbstractListChromosome<T> - Class in org.apache.commons.math.genetics
-
Chromosome represented by an immutable list of a fixed length.
- AbstractListChromosome(List<T>) - Constructor for class org.apache.commons.math.genetics.AbstractListChromosome
-
Constructor.
- AbstractListChromosome(T[]) - Constructor for class org.apache.commons.math.genetics.AbstractListChromosome
-
Constructor.
- AbstractMultipleLinearRegression - Class in org.apache.commons.math.stat.regression
-
Abstract base class for implementations of MultipleLinearRegression.
- AbstractMultipleLinearRegression() - Constructor for class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
- AbstractRandomGenerator - Class in org.apache.commons.math.random
-
- AbstractRandomGenerator() - Constructor for class org.apache.commons.math.random.AbstractRandomGenerator
-
Construct a RandomGenerator.
- AbstractRealMatrix - Class in org.apache.commons.math.linear
-
Basic implementation of RealMatrix methods regardless of the underlying storage.
- AbstractRealMatrix() - Constructor for class org.apache.commons.math.linear.AbstractRealMatrix
-
Creates a matrix with no data
- AbstractRealMatrix(int, int) - Constructor for class org.apache.commons.math.linear.AbstractRealMatrix
-
Create a new RealMatrix with the supplied row and column dimensions.
- AbstractRealVector - Class in org.apache.commons.math.linear
-
This class provides default basic implementations for many methods in the
RealVector interface.
- AbstractRealVector() - Constructor for class org.apache.commons.math.linear.AbstractRealVector
-
- AbstractRealVector.EntryImpl - Class in org.apache.commons.math.linear
-
An entry in the vector.
- AbstractRealVector.EntryImpl() - Constructor for class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
-
Simple constructor.
- AbstractRealVector.SparseEntryIterator - Class in org.apache.commons.math.linear
-
This class should rare be used, but is here to provide
a default implementation of sparseIterator(), which is implemented
by walking over the entries, skipping those whose values are the default one.
- AbstractRealVector.SparseEntryIterator() - Constructor for class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
-
Simple constructor.
- AbstractScalarDifferentiableOptimizer - Class in org.apache.commons.math.optimization.general
-
Base class for implementing optimizers for multivariate scalar functions.
- AbstractScalarDifferentiableOptimizer() - Constructor for class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Simple constructor with default settings.
- AbstractStepInterpolator - Class in org.apache.commons.math.ode.sampling
-
This abstract class represents an interpolator over the last step
during an ODE integration.
- AbstractStepInterpolator() - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Simple constructor.
- AbstractStepInterpolator(double[], boolean) - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Simple constructor.
- AbstractStepInterpolator(AbstractStepInterpolator) - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Copy constructor.
- AbstractStorelessUnivariateStatistic - Class in org.apache.commons.math.stat.descriptive
-
- AbstractStorelessUnivariateStatistic() - Constructor for class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
- AbstractUnivariateRealOptimizer - Class in org.apache.commons.math.optimization.univariate
-
Provide a default implementation for several functions useful to generic
optimizers.
- AbstractUnivariateRealOptimizer(int, double) - Constructor for class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Deprecated.
in 2.2. Please use the "setter" methods to assign meaningful
values to the maximum numbers of iterations and evaluations, and to the
absolute and relative accuracy thresholds.
- AbstractUnivariateRealOptimizer() - Constructor for class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Default constructor.
- AbstractUnivariateStatistic - Class in org.apache.commons.math.stat.descriptive
-
- AbstractUnivariateStatistic() - Constructor for class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
- AbstractWell - Class in org.apache.commons.math.random
-
This abstract class implements the WELL class of pseudo-random number generator
from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
- AbstractWell(int, int, int, int) - Constructor for class org.apache.commons.math.random.AbstractWell
-
Creates a new random number generator.
- AbstractWell(int, int, int, int, int) - Constructor for class org.apache.commons.math.random.AbstractWell
-
Creates a new random number generator using a single int seed.
- AbstractWell(int, int, int, int, int[]) - Constructor for class org.apache.commons.math.random.AbstractWell
-
Creates a new random number generator using an int array seed.
- AbstractWell(int, int, int, int, long) - Constructor for class org.apache.commons.math.random.AbstractWell
-
Creates a new random number generator using a single long seed.
- acceptStep(AbstractStepInterpolator, double[], double[], double) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Accept a step, triggering events and step handlers.
- accuracy - Variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
If the median residual at a certain robustness iteration
is less than this amount, no more iterations are done.
- ACOS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- acos() - Method in class org.apache.commons.math.complex.Complex
-
- acos(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the arc-cosine of the argument.
- acos(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the arc cosine of a number.
- acosh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the inverse hyperbolic cosine of a number.
- AdamsBashforthIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements explicit Adams-Bashforth integrators for Ordinary
Differential Equations.
- AdamsBashforthIntegrator(int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
-
Build an Adams-Bashforth integrator with the given order and step control parameters.
- AdamsBashforthIntegrator(int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
-
Build an Adams-Bashforth integrator with the given order and step control parameters.
- AdamsIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
- AdamsIntegrator(String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
-
Build an Adams integrator with the given order and step control prameters.
- AdamsIntegrator(String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
-
Build an Adams integrator with the given order and step control parameters.
- AdamsMoultonIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements implicit Adams-Moulton integrators for Ordinary
Differential Equations.
- AdamsMoultonIntegrator(int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
-
Build an Adams-Moulton integrator with the given order and error control parameters.
- AdamsMoultonIntegrator(int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
-
Build an Adams-Moulton integrator with the given order and error control parameters.
- AdamsMoultonIntegrator.Corrector - Class in org.apache.commons.math.ode.nonstiff
-
Corrector for current state in Adams-Moulton method.
- AdamsMoultonIntegrator.Corrector(double[], double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
-
Simple constructor.
- AdamsNordsieckTransformer - Class in org.apache.commons.math.ode.nonstiff
-
Transformer to Nordsieck vectors for Adams integrators.
- AdamsNordsieckTransformer(int) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Simple constructor.
- AdaptiveStepsizeIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This abstract class holds the common part of all adaptive
stepsize integrators for Ordinary Differential Equations.
- AdaptiveStepsizeIntegrator(String, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Build an integrator with the given stepsize bounds.
- AdaptiveStepsizeIntegrator(String, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Build an integrator with the given stepsize bounds.
- ADD - Static variable in class org.apache.commons.math.analysis.BinaryFunction
-
Deprecated.
- add(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function adding the instance and another function.
- add(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function adding a constant term to the instance.
- add(PolynomialFunction) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Add a polynomial to the instance.
- add(Complex) - Method in class org.apache.commons.math.complex.Complex
-
Return the sum of this complex number and the given complex number.
- add(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Add x to this.
- add(T) - Method in interface org.apache.commons.math.FieldElement
-
Compute this + a.
- add(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
-
Adds the value of this fraction to the passed BigInteger,
returning the result in reduced form.
- add(int) - Method in class org.apache.commons.math.fraction.BigFraction
-
Adds the value of this fraction to the passed integer, returning
the result in reduced form.
- add(long) - Method in class org.apache.commons.math.fraction.BigFraction
-
Adds the value of this fraction to the passed long, returning
the result in reduced form.
- add(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
-
Adds the value of this fraction to another, returning the result in
reduced form.
- add(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
-
Adds the value of this fraction to another, returning the result in reduced form.
- add(int) - Method in class org.apache.commons.math.fraction.Fraction
-
Add an integer to the fraction.
- add(Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
-
Add a vector to the instance.
- add(double, Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
-
Add a scaled vector to the instance.
- add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Compute the sum of this and m.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Compute the sum of this and m.
- add(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Compute the sum of this vector and v.
- add(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Compute the sum of this vector and v.
- add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Compute the sum of this and m.
- add(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Compute the sum of this and m.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Compute the sum of this and m.
- add(Array2DRowRealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Compute the sum of this and m.
- add(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute the sum of this and v.
- add(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute the sum of this and v.
- add(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute the sum of this and v.
- add(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Compute the sum of this vector and v.
- add(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Compute the sum of this vector and v.
- add(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Compute the sum of this and v.
- add(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Compute the sum of this and m.
- add(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Compute the sum of this and m.
- add(BigMatrixImpl) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Compute the sum of this and m.
- add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Compute the sum of this and m.
- add(BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Compute the sum of this and m.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Compute the sum of this and m.
- add(BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Compute the sum of this and m.
- add(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Compute the sum of this and m.
- add(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Compute the sum of this and v.
- add(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Compute the sum of this and v.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute the sum of this and m.
- add(OpenMapRealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute the sum of this and m.
- add(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Compute the sum of this vector and v.
- add(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to add two OpenMapRealVectors.
- add(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Compute the sum of this and m.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Compute the sum of this and m.
- add(RealMatrixImpl) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Compute the sum of this and m.
- add(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Compute the sum of this vector and v.
- add(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Compute the sum of this vector and v.
- add(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Optimized method to add sparse vectors.
- add(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Compute the sum of this and v.
- add(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Compute the sum of this and v.
- add(BigReal) - Method in class org.apache.commons.math.util.BigReal
-
Compute this + a.
- ADD_TRAP - Static variable in class org.apache.commons.math.dfp.Dfp
-
Name for traps triggered by addition.
- addAndCheck(int, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Add two integers, checking for overflow.
- addAndCheck(long, long) - Static method in class org.apache.commons.math.util.MathUtils
-
Add two long integers, checking for overflow.
- addAndCheck(long, long, Localizable) - Static method in class org.apache.commons.math.util.MathUtils
-
Add two long integers, checking for overflow.
- addChromosome(Chromosome) - Method in class org.apache.commons.math.genetics.ListPopulation
-
Add the given chromosome to the population.
- addChromosome(Chromosome) - Method in interface org.apache.commons.math.genetics.Population
-
Add the given chromosome to the population.
- addData(double, double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Adds the observation (x,y) to the regression data set.
- addData(double[][]) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Adds the observations represented by the elements in
data.
- addElement(double) - Method in interface org.apache.commons.math.util.DoubleArray
-
Adds an element to the end of this expandable array
- addElement(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Adds an element to the end of this expandable array.
- addElementRolling(double) - Method in interface org.apache.commons.math.util.DoubleArray
-
Adds an element to the end of the array and removes the first
element in the array.
- addElementRolling(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Adds an element to the end of the array and removes the first
element in the array.
- addElements(double[]) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Adds several element to the end of this expandable array.
- addEndTimeChecker(double, double, CombinedEventsManager) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Deprecated.
as of 2.2, this method is not used any more
- addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Add an event handler to the integrator.
- addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Add an events handler.
- addEventHandler(EventHandlerWithJacobians, double, double, int) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Add an event handler to the integrator.
- addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Add an event handler to the integrator.
- addEventHandler(EventHandler, double, double, int) - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Add an event handler to the integrator.
- ADDITIVE_MODE - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
-
additive expansion mode
- addMeasurement(WeightedMeasurement) - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Add a new measurement to the set.
- addObservedPoint(double, double) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Add an observed (x,y) point to the sample with unit weight.
- addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Add an observed weighted (x,y) point to the sample.
- addObservedPoint(WeightedObservedPoint) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Add an observed weighted (x,y) point to the sample.
- addObservedPoint(double, double) - Method in class org.apache.commons.math.optimization.fitting.GaussianFitter
-
Adds point (x, y) to list of observed points
with a weight of 1.0.
- addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.GaussianFitter
-
Adds point (x, y) to list of observed points
with a weight of weight.
- addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.HarmonicFitter
-
Add an observed weighted (x,y) point to the sample.
- addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter
-
Add an observed weighted (x,y) point to the sample.
- addParameter(EstimatedParameter) - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Add a parameter to the problem.
- addPoint(T) - Method in class org.apache.commons.math.stat.clustering.Cluster
-
Add a point to this cluster.
- addStepHandler(StepHandler) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Add a step handler to this integrator.
- addStepHandler(StepHandlerWithJacobians) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Add a step handler to this integrator.
- addStepHandler(StepHandler) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Add a step handler to this integrator.
- addStepHandler(StepHandler) - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Add a step handler to this integrator.
- addSub(Fraction, boolean) - Method in class org.apache.commons.math.fraction.Fraction
-
Implement add and subtract using algorithm described in Knuth 4.5.1.
- addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Change an entry in the specified row and column.
- addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Change an entry in the specified row and column.
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
-
Add a value to the data
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Adds the value to the dataset.
- addValue(double[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Add an n-tuple to the data
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Add a value to the data
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Adds the value to the dataset.
- addValue(double[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Add an n-tuple to the data
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Add a value to the data
- addValue(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- addValue(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Adds 1 to the frequency count for v.
- addValue(int) - Method in class org.apache.commons.math.stat.Frequency
-
Adds 1 to the frequency count for v.
- addValue(Integer) - Method in class org.apache.commons.math.stat.Frequency
-
Deprecated.
to be removed in math 3.0
- addValue(long) - Method in class org.apache.commons.math.stat.Frequency
-
Adds 1 to the frequency count for v.
- addValue(char) - Method in class org.apache.commons.math.stat.Frequency
-
Adds 1 to the frequency count for v.
- advance(AbstractRealVector.EntryImpl) - Method in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
-
Advance an entry up to the next nonzero one.
- advance() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
-
Advance iterator one step further.
- advance() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
-
Advance iterator one step further.
- after - Variable in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
-
Current state after correction.
- aggregate(Collection<SummaryStatistics>) - Static method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Computes aggregate summary statistics.
- aggregateStatistics - Variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
-
An additional SummaryStatistics into which values added to these
statistics (and possibly others) are aggregated
- AggregateSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
An aggregator for SummaryStatistics from several data sets or
data set partitions.
- AggregateSummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Initializes a new AggregateSummaryStatistics with default statistics
implementations.
- AggregateSummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Initializes a new AggregateSummaryStatistics with the specified statistics
object as a prototype for contributing statistics and for the internal
aggregate statistics.
- AggregateSummaryStatistics(SummaryStatistics, SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Initializes a new AggregateSummaryStatistics with the specified statistics
object as a prototype for contributing statistics and for the internal
aggregate statistics.
- AggregateSummaryStatistics.AggregatingSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
A SummaryStatistics that also forwards all values added to it to a second
SummaryStatistics for aggregation.
- AggregateSummaryStatistics.AggregatingSummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
-
Initializes a new AggregatingSummaryStatistics with the specified
aggregate statistics object
- AINV - Static variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
-
Matrix to compute the spline coefficients from the function values
and function derivatives values
- AINV - Static variable in class org.apache.commons.math.analysis.interpolation.TricubicSplineInterpolatingFunction
-
Matrix to compute the spline coefficients from the function values
and function derivatives values
- align(int) - Method in class org.apache.commons.math.dfp.Dfp
-
Make our exp equal to the supplied one, this may cause rounding.
- ALIGN_TRAP - Static variable in class org.apache.commons.math.dfp.Dfp
-
Name for traps triggered by alignment.
- alpha - Variable in class org.apache.commons.math.distribution.BetaDistributionImpl
-
First shape parameter.
- alpha - Variable in class org.apache.commons.math.distribution.GammaDistributionImpl
-
The shape parameter.
- angle(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
-
Compute the angular separation between two vectors.
- anovaFValue(Collection<double[]>) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
-
Computes the ANOVA F-value for a collection of double[]
arrays.
- anovaFValue(Collection<double[]>) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
-
Computes the ANOVA F-value for a collection of double[]
arrays.
- anovaPValue(Collection<double[]>) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
-
Computes the ANOVA P-value for a collection of double[]
arrays.
- anovaPValue(Collection<double[]>) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
-
Computes the ANOVA P-value for a collection of double[]
arrays.
- anovaStats(Collection<double[]>) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
-
This method actually does the calculations (except P-value).
- anovaTest(Collection<double[]>, double) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
-
Performs an ANOVA test, evaluating the null hypothesis that there
is no difference among the means of the data categories.
- anovaTest(Collection<double[]>, double) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
-
Performs an ANOVA test, evaluating the null hypothesis that there
is no difference among the means of the data categories.
- AnyMatrix - Interface in org.apache.commons.math.linear
-
Interface defining very basic matrix operations.
- append(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending a vector to this vector.
- append(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending a vector to this vector.
- append(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending a T to this vector.
- append(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending a T array to this vector.
- append(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending a vector to this vector.
- append(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending a vector to this vector.
- append(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending a double to this vector.
- append(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending a double array to this vector.
- append(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Construct a vector by appending a vector to this vector.
- append(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Construct a vector by appending a T to this vector.
- append(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Construct a vector by appending a T array to this vector.
- append(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to append a OpenMapRealVector.
- append(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Construct a vector by appending a vector to this vector.
- append(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Construct a vector by appending a double to this vector.
- append(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Construct a vector by appending a double array to this vector.
- append(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Construct a vector by appending a vector to this vector.
- append(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Construct a vector by appending a double to this vector.
- append(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Construct a vector by appending a double array to this vector.
- append(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Construct a vector by appending a vector to this vector.
- append(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Construct a vector by appending a vector to this vector.
- append(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Construct a vector by appending a T to this vector.
- append(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Construct a vector by appending a T array to this vector.
- append(ContinuousOutputModel) - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Append another model at the end of the instance.
- append(StringBuilder, double[], String, String, String) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Append a text representation of an array to a buffer.
- apply(double[], double[], double[][]) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
-
Compute the value of the bicubic polynomial.
- apply(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Apply the given statistic to the data associated with this set of statistics.
- apply(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Apply the given statistic to the data associated with this set of statistics.
- applyInverseTo(Vector3D) - Method in class org.apache.commons.math.geometry.Rotation
-
Apply the inverse of the rotation to a vector.
- applyInverseTo(Rotation) - Method in class org.apache.commons.math.geometry.Rotation
-
Apply the inverse of the instance to another rotation.
- applyTo(Vector3D) - Method in class org.apache.commons.math.geometry.Rotation
-
Apply the rotation to a vector.
- applyTo(Rotation) - Method in class org.apache.commons.math.geometry.Rotation
-
Apply the instance to another rotation.
- argument - Variable in exception org.apache.commons.math.exception.MathIllegalNumberException
-
Requested.
- argument - Variable in exception org.apache.commons.math.FunctionEvaluationException
-
Argument causing function evaluation failure
- ArgumentOutsideDomainException - Exception in org.apache.commons.math
-
Error thrown when a method is called with an out of bounds argument.
- ArgumentOutsideDomainException(double, double, double) - Constructor for exception org.apache.commons.math.ArgumentOutsideDomainException
-
Constructs an exception with specified formatted detail message.
- arguments - Variable in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Arguments used to build the message.
- arguments - Variable in exception org.apache.commons.math.exception.MathIllegalStateException
-
Arguments used to build the message.
- arguments - Variable in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Arguments used to build the message.
- arguments - Variable in exception org.apache.commons.math.MathException
-
Arguments used to build the message.
- arguments - Variable in exception org.apache.commons.math.MathRuntimeException
-
Arguments used to build the message.
- ArgUtils - Class in org.apache.commons.math.exception.util
-
Utility class for transforming the list of arguments passed to
constructors of exceptions.
- ArgUtils() - Constructor for class org.apache.commons.math.exception.util.ArgUtils
-
Private constructor
- arity - Variable in class org.apache.commons.math.genetics.TournamentSelection
-
number of chromosomes included in the tournament selections
- Array2DRowFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
Implementation of FieldMatrix
using a FieldElement[][] array to store entries.
- Array2DRowFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Creates a matrix with no data
- Array2DRowFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new FieldMatrix with the supplied row and column dimensions.
- Array2DRowFieldMatrix(T[][]) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new FieldMatrix using the input array as the underlying
data array.
- Array2DRowFieldMatrix(T[][], boolean) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new FieldMatrix using the input array as the underlying
data array.
- Array2DRowFieldMatrix(T[]) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new (column) FieldMatrix using v as the
data for the unique column of the v.length x 1 matrix
created.
- Array2DRowRealMatrix - Class in org.apache.commons.math.linear
-
Implementation of RealMatrix using a double[][] array to store entries and
LU decomposition to support linear system
solution and inverse.
- Array2DRowRealMatrix() - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Creates a matrix with no data
- Array2DRowRealMatrix(int, int) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new RealMatrix with the supplied row and column dimensions.
- Array2DRowRealMatrix(double[][]) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new RealMatrix using the input array as the underlying
data array.
- Array2DRowRealMatrix(double[][], boolean) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new RealMatrix using the input array as the underlying
data array.
- Array2DRowRealMatrix(double[]) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new (column) RealMatrix using v as the
data for the unique column of the v.length x 1 matrix
created.
- ArrayFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
- ArrayFieldVector(Field<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Build a 0-length vector.
- ArrayFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a (size)-length vector of zeros.
- ArrayFieldVector(int, T) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct an (size)-length vector with preset values.
- ArrayFieldVector(T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from an array, copying the input array.
- ArrayFieldVector(Field<T>, T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from an array, copying the input array.
- ArrayFieldVector(T[], boolean) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Create a new ArrayFieldVector using the input array as the underlying
data array.
- ArrayFieldVector(Field<T>, T[], boolean) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Create a new ArrayFieldVector using the input array as the underlying
data array.
- ArrayFieldVector(T[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from part of a array.
- ArrayFieldVector(FieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from another vector, using a deep copy.
- ArrayFieldVector(ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from another vector, using a deep copy.
- ArrayFieldVector(ArrayFieldVector<T>, boolean) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from another vector.
- ArrayFieldVector(ArrayFieldVector<T>, ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayFieldVector(ArrayFieldVector<T>, T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayFieldVector(T[], ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayFieldVector(T[], T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayFieldVector(Field<T>, T[], T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector - Class in org.apache.commons.math.linear
-
This class implements the
RealVector interface with a double array.
- ArrayRealVector() - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Build a 0-length vector.
- ArrayRealVector(int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a (size)-length vector of zeros.
- ArrayRealVector(int, double) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct an (size)-length vector with preset values.
- ArrayRealVector(double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from an array, copying the input array.
- ArrayRealVector(double[], boolean) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Create a new ArrayRealVector using the input array as the underlying
data array.
- ArrayRealVector(double[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from part of a array.
- ArrayRealVector(Double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from an array.
- ArrayRealVector(Double[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from part of a Double array
- ArrayRealVector(RealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from another vector, using a deep copy.
- ArrayRealVector(ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from another vector, using a deep copy.
- ArrayRealVector(ArrayRealVector, boolean) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from another vector.
- ArrayRealVector(ArrayRealVector, ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(ArrayRealVector, RealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(RealVector, ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(ArrayRealVector, double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(double[], ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(double[], double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- asCollector(BivariateRealFunction, double) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Generates a function that iteratively apply instance function on all
elements of an array.
- asCollector(BivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Generates a function that iteratively apply instance function on all
elements of an array.
- asCollector(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Generates a function that iteratively apply instance function on all
elements of an array.
- asCollector() - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Generates a function that iteratively apply instance function on all
elements of an array.
- ASIN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- asin() - Method in class org.apache.commons.math.complex.Complex
-
- asin(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the arc-sine of the argument.
- asin(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the arc sine of a number.
- asinh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the inverse hyperbolic sine of a number.
- assignPointsToClusters(Collection<Cluster<T>>, Collection<T>) - Static method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Adds the given points to the closest
Cluster.
- ATAN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- atan() - Method in class org.apache.commons.math.complex.Complex
-
- atan(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the arc tangent of the argument
Uses the typical taylor series
but may reduce arguments using the following identity
tan(x+y) = (tan(x) + tan(y)) / (1 - tan(x)*tan(y))
since tan(PI/8) = sqrt(2)-1,
atan(x) = atan( (x - sqrt(2) + 1) / (1+x*sqrt(2) - x) + PI/8.0
- atan(double) - Static method in class org.apache.commons.math.util.FastMath
-
Arctangent function
- atan(double, double, boolean) - Static method in class org.apache.commons.math.util.FastMath
-
Internal helper function to compute arctangent.
- ATAN2 - Static variable in class org.apache.commons.math.analysis.BinaryFunction
-
Deprecated.
- atan2(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Two arguments arctangent function
- atanh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the inverse hyperbolic tangent of a number.
- atanInternal(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the arc-tangent of the argument.
- c - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Centers of the Newton polynomial.
- c - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Time steps from Butcher array (without the first zero).
- c - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
-
Time steps from Butcher array (without the first zero).
- c - Variable in class org.apache.commons.math.optimization.fitting.GaussianDerivativeFunction
-
Parameter c of this function.
- c - Variable in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Parameter c of this function.
- c1 - Variable in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Update coefficients of the higher order derivatives wrt y'.
- C14 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
-
Time step for stage 14 (interpolation only).
- C15 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
-
Time step for stage 15 (interpolation only).
- C16 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
-
Time step for stage 16 (interpolation only).
- C_LIMIT - Static variable in class org.apache.commons.math.special.Gamma
-
C limit.
- CACHE - Static variable in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Cache for already computed coefficients.
- cachedB - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Cached value of B.
- cachedD - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Cached value of D.
- cachedH - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
-
Cached value of H.
- cachedL - Variable in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Cached value of L.
- cachedL - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Cached value of L.
- cachedL - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
-
Cached value of L.
- cachedLT - Variable in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Cached value of LT.
- cachedNormalDeviate - Variable in class org.apache.commons.math.random.AbstractRandomGenerator
-
Cached random normal value.
- cachedP - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Cached value of P.
- cachedP - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
-
Cached value of P.
- cachedPivots - Variable in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Cached pivots.
- cachedQ - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
-
Cached value of Q.
- cachedQ - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Cached value of Q.
- cachedQT - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
-
Cached value of QT.
- cachedQt - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Cached value of Qt.
- cachedR - Variable in class org.apache.commons.math.linear.QRDecompositionImpl
-
Cached value of R.
- cachedS - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Cached value of S.
- cachedT - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Cached value of T.
- cachedU - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Cached value of U.
- cachedU - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Cached value of U.
- cachedU - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
-
Cached value of U.
- cachedU - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Cached value of U.
- cachedUt - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Cached value of UT.
- cachedV - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Cached value of V.
- cachedV - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Cached value of V.
- cachedV - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Cached value of V.
- cachedVt - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Cached value of Vt.
- cachedVt - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Cached value of VT.
- calculateAdjustedRSquared() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Returns the adjusted R-squared statistic, defined by the formula
- calculateBeta() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the beta of multiple linear regression in matrix notation.
- calculateBeta() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Calculates beta by GLS.
- calculateBeta() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Calculates the regression coefficients using OLS.
- calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the beta variance of multiple linear regression in matrix
notation.
- calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Calculates the variance on the beta.
- calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Calculates the variance-covariance matrix of the regression parameters.
- calculateErrorVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the variance of the error term.
- calculateErrorVariance() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Calculates the estimated variance of the error term using the formula
- calculateHat() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Compute the "hat" matrix.
- calculateNumericalMean() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Calculates the mean.
- calculateNumericalVariance() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Calculates the variance.
- calculateResiduals() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the residuals of multiple linear regression in matrix
notation.
- calculateResidualSumOfSquares() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Returns the sum of squared residuals.
- calculateRSquared() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Returns the R-Squared statistic, defined by the formula
- calculateTotalSumOfSquares() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Returns the sum of squared deviations of Y from its mean.
- calculateYVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the variance of the y values.
- CardanEulerSingularityException - Exception in org.apache.commons.math.geometry
-
This class represents exceptions thrown while extractiong Cardan
or Euler angles from a rotation.
- CardanEulerSingularityException(boolean) - Constructor for exception org.apache.commons.math.geometry.CardanEulerSingularityException
-
Simple constructor.
- CauchyDistribution - Interface in org.apache.commons.math.distribution
-
Cauchy Distribution.
- CauchyDistributionImpl - Class in org.apache.commons.math.distribution
-
- CauchyDistributionImpl() - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Creates cauchy distribution with the medain equal to zero and scale
equal to one.
- CauchyDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Create a cauchy distribution using the given median and scale.
- CauchyDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Create a cauchy distribution using the given median and scale.
- CBRT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- cbrt(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the cubic root of a number.
- CBRTTWO - Static variable in class org.apache.commons.math.util.FastMath
-
Table of 2^((n+2)/3)
- CEIL - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- ceil() - Method in class org.apache.commons.math.dfp.Dfp
-
Round to an integer using the round ceil mode.
- ceil(double) - Static method in class org.apache.commons.math.util.FastMath
-
Get the smallest whole number larger than x.
- center - Variable in class org.apache.commons.math.stat.clustering.Cluster
-
Center of the cluster.
- centroidOf(Collection<T>) - Method in interface org.apache.commons.math.stat.clustering.Clusterable
-
Returns the centroid of the given Collection of points.
- centroidOf(Collection<EuclideanIntegerPoint>) - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
-
Returns the centroid of the given Collection of points.
- changeIndexSign(int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Change the index sign
- changeIndexSign(int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Change the index sign
- CHEBYSHEV_COEFFICIENTS - Static variable in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Coefficients for Chebyshev polynomials.
- checkAdditionCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a matrix is addition compatible with the instance
- checkAdditionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if matrices are addition compatible
- checkAllFiniteReal(double[], Localizable) - Static method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
Check that all elements of an array are finite real numbers.
- checkArray(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Checks to make sure that the input long[][] array is rectangular,
has at least 2 rows and 2 columns, and has all non-negative entries,
throwing IllegalArgumentException if any of these checks fail.
- checkBinomial(int, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Check binomial preconditions.
- checkColumnIndex(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a column index is valid.
- checkColumnIndex(AnyMatrix, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if a column index is valid.
- checkContractExpand(float, float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Checks the expansion factor and the contraction criteria and throws an
IllegalArgumentException if the contractionCriteria is less than the
expansionCriteria
- checkDimension(int, Object) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Check array dimensions.
- checkDimension(int) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Throws DimensionMismatchException if dimension != k.
- checkedCumulativeProbability(int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Computes the cumulative probability function and checks for NaN values returned.
- checkEmpty() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Throws IllegalStateException if n > 0.
- checkEmpty() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Throws IllegalStateException if n > 0.
- checkEmpty() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Throws IllegalStateException if n > 0.
- checker - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Convergence checker.
- checker - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Convergence checker.
- checker - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Deprecated.
- checkIndex(int) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Check if an index is valid.
- checkIndex(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Check if an index is valid.
- checkIndex(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Check if an index is valid.
- checkMultiplicationCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a matrix is multiplication compatible with the instance
- checkMultiplicationCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if matrices are multiplication compatible
- checkNonNegative(long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Check all entries of the input array are >= 0.
- checkNonNegative(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Check all entries of the input array are >= 0.
- checkOrder(double[], MathUtils.OrderDirection, boolean) - Static method in class org.apache.commons.math.util.MathUtils
-
Checks that the given array is sorted.
- checkOrder(double[]) - Static method in class org.apache.commons.math.util.MathUtils
-
Checks that the given array is sorted in strictly increasing order.
- checkOrder(double[], int, boolean) - Static method in class org.apache.commons.math.util.MathUtils
-
Deprecated.
as of 2.2 (please use the new checkOrder method). To be removed in 3.0.
- checkPositive(double[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Check all entries of the input array are > 0.
- checkRectangular(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Throws IllegalArgumentException if the input array is not rectangular.
- checkResultComputed() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Check if a result has been computed.
- checkResultComputed() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Deprecated.
in 2.2 (no alternative).
- checkRowIndex(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a row index is valid.
- checkRowIndex(AnyMatrix, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if a row index is valid.
- checkSampleData(double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
-
Check sample data.
- checkSampleData(StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
-
Check sample data.
- checkSignificanceLevel(double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
-
Check significance level.
- checkStrictlyIncreasing(double[]) - Static method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
Check that elements of the abscissae array are in a strictly
increasing order.
- checkSubMatrixIndex(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if submatrix ranges indices are valid.
- checkSubMatrixIndex(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if submatrix ranges indices are valid.
- checkSubMatrixIndex(AnyMatrix, int, int, int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if submatrix ranges indices are valid.
- checkSubMatrixIndex(AnyMatrix, int[], int[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if submatrix ranges indices are valid.
- checkSubtractionCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a matrix is subtraction compatible with the instance
- checkSubtractionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if matrices are subtraction compatible
- checkSufficientData(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Throws IllegalArgumentException of the matrix does not have at least
two columns and two rows
- checkSufficientData(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Throws IllegalArgumentException of the matrix does not have at least
two columns and two rows
- checkValidity(List<T>) - Method in class org.apache.commons.math.genetics.AbstractListChromosome
-
Asserts that representation can represent a valid chromosome.
- checkValidity(List<Integer>) - Method in class org.apache.commons.math.genetics.BinaryChromosome
-
Asserts that representation can represent a valid chromosome.
- checkValidity(List<Double>) - Method in class org.apache.commons.math.genetics.RandomKey
-
Asserts that representation can represent a valid chromosome.
- checkVectorDimensions(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Check if instance and specified vectors have the same dimension.
- checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Check if instance dimension is equal to some expected value.
- checkVectorDimensions(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Check if instance and specified vectors have the same dimension.
- checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Check if instance dimension is equal to some expected value.
- checkVectorDimensions(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Check if instance and specified vectors have the same dimension.
- checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Check if instance dimension is equal to some expected value.
- checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Check if instance dimension is equal to some expected value.
- chiSquare(double[], long[]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
- chiSquare(long[][]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
- chiSquare(double[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquare(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquare(double[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquare(long[][]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareDataSetsComparison(long[], long[]) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
-
- ChiSquaredDistribution - Interface in org.apache.commons.math.distribution
-
The Chi-Squared Distribution.
- ChiSquaredDistributionImpl - Class in org.apache.commons.math.distribution
-
- ChiSquaredDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Create a Chi-Squared distribution with the given degrees of freedom.
- ChiSquaredDistributionImpl(double, GammaDistribution) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Deprecated.
as of 2.1 (to avoid possibly inconsistent state, the
"GammaDistribution" will be instantiated internally)
- ChiSquaredDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Create a Chi-Squared distribution with the given degrees of freedom and
inverse cumulative probability accuracy.
- ChiSquareTest - Interface in org.apache.commons.math.stat.inference
-
An interface for Chi-Square tests.
- chiSquareTest(double[], long[]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
- chiSquareTest(double[], long[], double) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
Performs a
Chi-square goodness of fit test evaluating the null hypothesis that the observed counts
conform to the frequency distribution described by the expected counts, with
significance level
alpha.
- chiSquareTest(long[][]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
- chiSquareTest(long[][], double) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
Performs a
chi-square test of independence evaluating the null hypothesis that the classifications
represented by the counts in the columns of the input 2-way table are independent of the rows,
with significance level
alpha.
- chiSquareTest(double[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTest(double[], long[], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Performs a
Chi-square goodness of fit test evaluating the null hypothesis that the observed counts
conform to the frequency distribution described by the expected counts, with
significance level
alpha.
- chiSquareTest(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTest(long[][], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTest - Static variable in class org.apache.commons.math.stat.inference.TestUtils
-
Singleton ChiSquareTest instance using default implementation.
- chiSquareTest(double[], long[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTest(double[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTest(long[][], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTest(long[][]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTestDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTestDataSetsComparison(long[], long[], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTestDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTestDataSetsComparison(long[], long[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTestDataSetsComparison(long[], long[]) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
-
Returns the
observed significance level, or
p-value, associated with a Chi-Square two sample test comparing
bin frequency counts in
observed1 and
observed2.
- chiSquareTestDataSetsComparison(long[], long[], double) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
-
Performs a Chi-Square two sample test comparing two binned data
sets.
- ChiSquareTestImpl - Class in org.apache.commons.math.stat.inference
-
- ChiSquareTestImpl() - Constructor for class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Construct a ChiSquareTestImpl
- ChiSquareTestImpl(ChiSquaredDistribution) - Constructor for class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Create a test instance using the given distribution for computing
inference statistics.
- CholeskyDecomposition - Interface in org.apache.commons.math.linear
-
An interface to classes that implement an algorithm to calculate the
Cholesky decomposition of a real symmetric positive-definite matrix.
- CholeskyDecompositionImpl - Class in org.apache.commons.math.linear
-
Calculates the Cholesky decomposition of a matrix.
- CholeskyDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Calculates the Cholesky decomposition of the given matrix.
- CholeskyDecompositionImpl(RealMatrix, double, double) - Constructor for class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Calculates the Cholesky decomposition of the given matrix.
- CholeskyDecompositionImpl.Solver - Class in org.apache.commons.math.linear
-
Specialized solver.
- CholeskyDecompositionImpl.Solver(double[][]) - Constructor for class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
-
Build a solver from decomposed matrix.
- chooseInitialCenters(Collection<T>, int, Random) - Static method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Use K-means++ to choose the initial centers.
- Chromosome - Class in org.apache.commons.math.genetics
-
Individual in a population.
- Chromosome() - Constructor for class org.apache.commons.math.genetics.Chromosome
-
- ChromosomePair - Class in org.apache.commons.math.genetics
-
- ChromosomePair(Chromosome, Chromosome) - Constructor for class org.apache.commons.math.genetics.ChromosomePair
-
Create a chromosome pair.
- chromosomes - Variable in class org.apache.commons.math.genetics.ListPopulation
-
List of chromosomes
- classes() - Method in class org.apache.commons.math.util.TransformerMap
-
Returns the Set of Classes used as keys in the map.
- ClassicalRungeKuttaIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements the classical fourth order Runge-Kutta
integrator for Ordinary Differential Equations (it is the most
often used Runge-Kutta method).
- ClassicalRungeKuttaIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
-
Simple constructor.
- ClassicalRungeKuttaStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements a step interpolator for the classical fourth
order Runge-Kutta integrator.
- ClassicalRungeKuttaStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
-
Simple constructor.
- ClassicalRungeKuttaStepInterpolator(ClassicalRungeKuttaStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
-
Copy constructor.
- classify() - Method in class org.apache.commons.math.dfp.Dfp
-
Returns the type - one of FINITE, INFINITE, SNAN, QNAN.
- clear() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
- clear() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Clears the internal state of the Statistic
- clear() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.Frequency
-
Clears the frequency table
- clear() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Clears all data from the model.
- clear() - Method in interface org.apache.commons.math.util.DoubleArray
-
Clear the double array
- clear() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Clear the array, reset the size to the initialCapacity and the number
of elements to zero.
- clear() - Method in class org.apache.commons.math.util.TransformerMap
-
Clears all the Class to Transformer mappings.
- clearEventHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Remove all the event handlers that have been added to the integrator.
- clearEventHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Remove all the event handlers that have been added to the integrator.
- clearEventHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Remove all the event handlers that have been added to the integrator.
- clearEventsHandlers() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Remove all the events handlers that have been added to the manager.
- clearIEEEFlags() - Method in class org.apache.commons.math.dfp.DfpField
-
Clears the IEEE 854 status flags.
- clearObservations() - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Remove all observations.
- clearObservations() - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter
-
Remove all observations.
- clearResult() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Convenience function for implementations.
- clearResult() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Convenience function for implementations.
- clearResult() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Deprecated.
in 2.2 (no alternative).
- clearStepHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Remove all the step handlers that have been added to the integrator.
- clearStepHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Remove all the step handlers that have been added to the integrator.
- clearStepHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Remove all the step handlers that have been added to the integrator.
- clone() - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
- clone(FastFourierTransformer.MultiDimensionalComplexMatrix) - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
-
Copy contents of current array into mdcm.
- closeReplayFile() - Method in class org.apache.commons.math.random.ValueServer
-
Closes valuesFileURL after use in REPLAY_MODE.
- Cluster<T extends Clusterable<T>> - Class in org.apache.commons.math.stat.clustering
-
- Cluster(T) - Constructor for class org.apache.commons.math.stat.clustering.Cluster
-
Build a cluster centered at a specified point.
- cluster(Collection<T>, int, int) - Method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Runs the K-means++ clustering algorithm.
- Clusterable<T> - Interface in org.apache.commons.math.stat.clustering
-
Interface for points that can be clustered together.
- coeff - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
extrapolation coefficients.
- coefficients - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
The coefficients of the polynomial, ordered by degree -- i.e.,
coefficients[0] is the constant term and coefficients[n] is the
coefficient of x^n where n is the degree of the polynomial.
- coefficients - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
The coefficients of the polynomial, ordered by degree -- i.e.
- coefficients - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
The coefficients of the polynomial, ordered by degree -- i.e.
- coefficients - Variable in class org.apache.commons.math.optimization.linear.LinearConstraint
-
Coefficients of the constraint (left hand side).
- coefficients - Variable in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Coefficients of the constraint (ci).
- coefficientsComputed - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Whether the polynomial coefficients are available.
- coefficientsComputed - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Whether the polynomial coefficients are available.
- cols - Variable in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Number of columns of the jacobian matrix.
- cols - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Number of columns of the jacobian matrix.
- columnLabels - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
-
The variables each column represents
- columns - Variable in class org.apache.commons.math.linear.BlockFieldMatrix
-
Number of columns of the matrix.
- columns - Variable in class org.apache.commons.math.linear.BlockRealMatrix
-
Number of columns of the matrix.
- columns - Variable in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Number of columns of the matrix.
- columns - Variable in class org.apache.commons.math.linear.SparseFieldMatrix
-
column dimension
- combine(UnivariateRealFunction, BivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function combining the instance and another function.
- CombinedEventsManager - Class in org.apache.commons.math.ode.events
-
Deprecated.
as of 2.2, this class is not used anymore
- CombinedEventsManager() - Constructor for class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Simple constructor.
- comparatorPermutation(List<S>, Comparator<S>) - Static method in class org.apache.commons.math.genetics.RandomKey
-
Generates a representation of a permutation corresponding to the
data sorted by comparator.
- compare(Dfp, Dfp) - Static method in class org.apache.commons.math.dfp.Dfp
-
Compare two instances.
- compare(Comparable<T>, Comparable<T>) - Method in class org.apache.commons.math.stat.Frequency.NaturalComparator
-
Compare the two Comparable arguments.
- compareTo(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
-
Compares this object to another based on size.
- compareTo(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
-
Compares this object to another based on size.
- compareTo(Chromosome) - Method in class org.apache.commons.math.genetics.Chromosome
-
Compares two chromosomes based on their fitness.
- compareTo(NaturalRanking.IntDoublePair) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
-
Compare this IntDoublePair to another pair.
- compareTo(BigReal) - Method in class org.apache.commons.math.util.BigReal
- compareTo(double, double, double) - Static method in class org.apache.commons.math.util.MathUtils
-
Compares two numbers given some amount of allowed error.
- complement(int) - Method in class org.apache.commons.math.dfp.Dfp
-
Negate the mantissa of this by computing the complement.
- Complex - Class in org.apache.commons.math.complex
-
Representation of a Complex number - a number which has both a
real and imaginary part.
- Complex(double, double) - Constructor for class org.apache.commons.math.complex.Complex
-
Create a complex number given the real and imaginary parts.
- ComplexField - Class in org.apache.commons.math.complex
-
Representation of the complex numbers field.
- ComplexField() - Constructor for class org.apache.commons.math.complex.ComplexField
-
Private constructor for the singleton.
- ComplexField.LazyHolder - Class in org.apache.commons.math.complex
-
Holder for the instance.
- ComplexField.LazyHolder() - Constructor for class org.apache.commons.math.complex.ComplexField.LazyHolder
-
- ComplexFormat - Class in org.apache.commons.math.complex
-
Formats a Complex number in cartesian format "Re(c) + Im(c)i".
- ComplexFormat() - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with the default imaginary character, 'i', and the
default number format for both real and imaginary parts.
- ComplexFormat(NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom number format for both real and
imaginary parts.
- ComplexFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom number format for the real part and a
custom number format for the imaginary part.
- ComplexFormat(String) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom imaginary character, and the default
number format for both real and imaginary parts.
- ComplexFormat(String, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom imaginary character, and a custom number
format for both real and imaginary parts.
- ComplexFormat(String, NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom imaginary character, a custom number
format for the real part, and a custom number format for the imaginary
part.
- ComplexUtils - Class in org.apache.commons.math.complex
-
Static implementations of common
Complex utilities functions.
- ComplexUtils() - Constructor for class org.apache.commons.math.complex.ComplexUtils
-
Default constructor.
- ComposableFunction - Class in org.apache.commons.math.analysis
-
- ComposableFunction() - Constructor for class org.apache.commons.math.analysis.ComposableFunction
-
- CompositeFormat - Class in org.apache.commons.math.util
-
Base class for formatters of composite objects (complex numbers, vectors ...).
- CompositeFormat() - Constructor for class org.apache.commons.math.util.CompositeFormat
-
- computeBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
-
Compute bin stats.
- computeBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapter
-
Compute bin stats.
- computeBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
-
Compute bin stats.
- computeCapacity(int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Compute the capacity needed for a given size.
- computeCapacity(int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Compute the capacity needed for a given size.
- computeCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Calculate the coefficients of Lagrange polynomial from the
interpolation data.
- computeCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Calculate the normal polynomial coefficients given the Newton form.
- computeCoefficients(int, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Compute the interpolation coefficients for dense output.
- computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Computes the correlation matrix for the columns of the
input matrix.
- computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Computes the correlation matrix for the columns of the
input rectangular array.
- computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Computes the Spearman's rank correlation matrix for the columns of the
input matrix.
- computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Computes the Spearman's rank correlation matrix for the columns of the
input rectangular array.
- computeCovarianceMatrix(RealMatrix, boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Compute a covariance matrix from a matrix whose columns represent
covariates.
- computeCovarianceMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Create a covariance matrix from a matrix whose columns represent
covariates.
- computeCovarianceMatrix(double[][], boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Compute a covariance matrix from a rectangular array whose columns represent
covariates.
- computeCovarianceMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Create a covariance matrix from a rectangual array whose columns represent
covariates.
- computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Compute the derivatives and check the number of evaluations.
- computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.FirstOrderConverter
-
Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[]) - Method in interface org.apache.commons.math.ode.FirstOrderDifferentialEquations
-
Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
-
Deprecated.
Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
-
Deprecated.
Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.MultistepIntegrator.CountingDifferentialEquations
-
Get the current time derivative of the state vector.
- computeDistribution() - Method in class org.apache.commons.math.random.ValueServer
-
Computes the empirical distribution using values from the file
in valuesFileURL, using the default number of bins.
- computeDistribution(int) - Method in class org.apache.commons.math.random.ValueServer
-
Computes the empirical distribution using values from the file
in valuesFileURL and binCount bins.
- computeDividedDifference(double[], double[]) - Static method in class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
-
Returns a copy of the divided difference array.
- computeExp(Dfp, Dfp) - Static method in class org.apache.commons.math.dfp.DfpField
-
Compute exp(a).
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.HighamHall54StepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.nonstiff.ThreeEighthesStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
-
Compute the state at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeJacobians(double, double[], double[], double[][], double[][]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
-
Deprecated.
Compute the partial derivatives of ODE with respect to state.
- computeJacobians(double, double[], double[], double[][], double[][]) - Method in interface org.apache.commons.math.ode.jacobians.ODEWithJacobians
-
Deprecated.
Compute the partial derivatives of ODE with respect to state.
- computeKey(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute the key to access a matrix element
- computeKey(int, int) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Compute the key to access a matrix element
- computeLn(Dfp, Dfp, Dfp) - Static method in class org.apache.commons.math.dfp.DfpField
-
Compute ln(a).
- computeObjectiveGradient(double[]) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Compute the gradient vector.
- computeObjectiveValue(double[]) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Compute the objective function value.
- computeObjectiveValue(UnivariateRealFunction, double) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- computeObjectiveValue(double) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Compute the objective function value.
- computeOmega(int) - Method in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
-
Computes the nth roots of unity.
- computePartialDerivatives() - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
-
Compute all partial derivatives functions.
- computePartialDerivatives() - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
-
Compute all partial derivatives.
- computePi(Dfp, Dfp, Dfp) - Static method in class org.apache.commons.math.dfp.DfpField
-
Compute π using Jonathan and Peter Borwein quartic formula.
- computeSecondDerivatives(double, double[], double[], double[]) - Method in interface org.apache.commons.math.ode.SecondOrderDifferentialEquations
-
Get the current time derivative of the state vector.
- computeSplineCoefficients(double[]) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
-
Compute the spline coefficients from the list of function values and
function partial derivatives values at the four corners of a grid
element.
- computeSplineCoefficients(double[]) - Method in class org.apache.commons.math.analysis.interpolation.TricubicSplineInterpolatingFunction
-
Compute the spline coefficients from the list of function values and
function partial derivatives values at the four corners of a grid
element.
- computeStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
-
Compute sample statistics.
- computeStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapter
-
Compute sample statistics.
- computeStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
-
Compute sample statistics.
- computeStepGrowShrinkFactor(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Compute step grow/shrink factor according to normalized error.
- computeStringConstants(int) - Static method in class org.apache.commons.math.dfp.DfpField
-
Recompute the high precision string constants.
- computeUpToDegree(int, int, PolynomialsUtils.RecurrenceCoefficientsGenerator, ArrayList<BigFraction>) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Compute polynomial coefficients up to a given degree.
- conjugate() - Method in class org.apache.commons.math.complex.Complex
-
Return the conjugate of this complex number.
- ConjugateGradientFormula - Enum in org.apache.commons.math.optimization.general
-
- ConjugateGradientFormula() - Constructor for enum org.apache.commons.math.optimization.general.ConjugateGradientFormula
-
- CONSTANT_MODE - Static variable in class org.apache.commons.math.random.ValueServer
-
Always return mu
- constantTerm - Variable in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Constant term of the linear equation.
- constraints - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Linear constraints.
- containsClass(Class<?>) - Method in class org.apache.commons.math.util.TransformerMap
-
Tests if a Class is present in the TransformerMap.
- containsKey(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Check if a value is associated with a key.
- containsKey(int, int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Check if the tables contain an element associated with specified key
at specified index.
- containsKey(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Check if a value is associated with a key.
- containsKey(int, int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Check if the tables contain an element associated with specified key
at specified index.
- containsNaNs(NaturalRanking.IntDoublePair[]) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
-
Checks for presence of NaNs in ranks.
- containsTransformer(NumberTransformer) - Method in class org.apache.commons.math.util.TransformerMap
-
Tests if a NumberTransformer is present in the TransformerMap.
- CONTINUE - Static variable in interface org.apache.commons.math.ode.events.EventHandler
-
Continue indicator.
- CONTINUE - Static variable in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
-
Deprecated.
Continue indicator.
- ContinuedFraction - Class in org.apache.commons.math.util
-
Provides a generic means to evaluate continued fractions.
- ContinuedFraction() - Constructor for class org.apache.commons.math.util.ContinuedFraction
-
Default constructor.
- ContinuousDistribution - Interface in org.apache.commons.math.distribution
-
Base interface for continuous distributions.
- ContinuousOutputModel - Class in org.apache.commons.math.ode
-
This class stores all information provided by an ODE integrator
during the integration process and build a continuous model of the
solution from this.
- ContinuousOutputModel() - Constructor for class org.apache.commons.math.ode.ContinuousOutputModel
-
Simple constructor.
- contract() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Contracts the storage array to the (size of the element set) + 1 - to
avoid a zero length array.
- contractionCriteria - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
The contraction criteria determines when the internal array will be
contracted to fit the number of elements contained in the element
array + 1.
- converged(int, RealPointValuePair, RealPointValuePair) - Method in interface org.apache.commons.math.optimization.RealConvergenceChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, RealPointValuePair, RealPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleRealPointChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, RealPointValuePair, RealPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleScalarValueChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleVectorialPointChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleVectorialValueChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in interface org.apache.commons.math.optimization.VectorialConvergenceChecker
-
Check if the optimization algorithm has converged considering the last points.
- convergence - Variable in class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Threshold for cost convergence.
- convergence - Variable in class org.apache.commons.math.ode.events.EventState
-
Convergence threshold for event localization.
- ConvergenceException - Exception in org.apache.commons.math
-
Error thrown when a numerical computation can not be performed because the
numerical result failed to converge to a finite value.
- ConvergenceException() - Constructor for exception org.apache.commons.math.ConvergenceException
-
Default constructor.
- ConvergenceException(String, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
-
- ConvergenceException(Localizable, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
-
Constructs an exception with specified formatted detail message.
- ConvergenceException(Throwable) - Constructor for exception org.apache.commons.math.ConvergenceException
-
Create an exception with a given root cause.
- ConvergenceException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
-
- ConvergenceException(Throwable, Localizable, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
-
Constructs an exception with specified formatted detail message and root cause.
- ConvergenceException - Exception in org.apache.commons.math.exception
-
Error thrown when a numerical computation can not be performed because the
numerical result failed to converge to a finite value.
- ConvergenceException() - Constructor for exception org.apache.commons.math.exception.ConvergenceException
-
Construct the exception.
- ConvergenceException(Localizable) - Constructor for exception org.apache.commons.math.exception.ConvergenceException
-
Construct the exception with a specific context.
- ConvergenceException(Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.ConvergenceException
-
Construct the exception with a specific context and arguments.
- ConvergingAlgorithm - Interface in org.apache.commons.math
-
Deprecated.
in 2.2 (to be removed in 3.0). The concept of "iteration" will
be moved to a new IterativeAlgorithm. The concept of "accuracy" is
currently is also contained in SimpleRealPointChecker
and similar classes.
- ConvergingAlgorithmImpl - Class in org.apache.commons.math
-
Deprecated.
in 2.2 (to be removed in 3.0).
- ConvergingAlgorithmImpl(int, double) - Constructor for class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
in 2.2. Derived classes should use the "setter" methods
in order to assign meaningful values to all the instances variables.
- ConvergingAlgorithmImpl() - Constructor for class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
in 2.2 (to be removed as soon as the single non-default one
has been removed).
- copy() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns a (deep) copy of this vector.
- copy() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns a (deep) copy of this vector.
- copy() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Create a new BigMatrix which is a copy of this.
- copy() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in interface org.apache.commons.math.linear.FieldVector
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Returns a (deep) copy of this vector.
- copy() - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns a (deep) copy of this.
- copy() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns a (deep) copy of this vector.
- copy() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Copy the instance.
- copy() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Copy the instance.
- copy() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Copy the instance.
- copy() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Copy the instance.
- copy() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
Returns a copy of the statistic with the same internal state.
- copy() - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Returns a copy of the statistic with the same internal state.
- copy() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns a copy of this DescriptiveStatistics instance with the same internal state.
- copy(DescriptiveStatistics, DescriptiveStatistics) - Static method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Returns a copy of the statistic with the same internal state.
- copy(FirstMoment, FirstMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Returns a copy of the statistic with the same internal state.
- copy(FourthMoment, FourthMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns a copy of the statistic with the same internal state.
- copy(GeometricMean, GeometricMean) - Static method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Returns a copy of the statistic with the same internal state.
- copy(Kurtosis, Kurtosis) - Static method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns a copy of the statistic with the same internal state.
- copy(Mean, Mean) - Static method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Returns a copy of the statistic with the same internal state.
- copy(SecondMoment, SecondMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns a copy of the statistic with the same internal state.
- copy(SemiVariance, SemiVariance) - Static method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Returns a copy of the statistic with the same internal state.
- copy(Skewness, Skewness) - Static method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns a copy of the statistic with the same internal state.
- copy(StandardDeviation, StandardDeviation) - Static method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Returns a copy of the statistic with the same internal state.
- copy(ThirdMoment, ThirdMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns a copy of the statistic with the same internal state.
- copy(Variance, Variance) - Static method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Returns a copy of the statistic with the same internal state.
- copy(Max, Max) - Static method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Returns a copy of the statistic with the same internal state.
- copy(Min, Min) - Static method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Returns a copy of the statistic with the same internal state.
- copy(Percentile, Percentile) - Static method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Copies source to dest.
- copy() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Returns a copy of the statistic with the same internal state.
- copy() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns a copy of the statistic with the same internal state.
- copy(Product, Product) - Static method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Returns a copy of the statistic with the same internal state.
- copy(Sum, Sum) - Static method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Returns a copy of the statistic with the same internal state.
- copy(SumOfLogs, SumOfLogs) - Static method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Returns a copy of the statistic with the same internal state.
- copy(SumOfSquares, SumOfSquares) - Static method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns a copy of this SummaryStatistics instance with the same internal state.
- copy(SummaryStatistics, SummaryStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns a copy of this SynchronizedDescriptiveStatistics instance with the
same internal state.
- copy(SynchronizedDescriptiveStatistics, SynchronizedDescriptiveStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns a copy of this SynchronizedSummaryStatistics instance with the
same internal state.
- copy(SynchronizedSummaryStatistics, SynchronizedSummaryStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Copies source to dest.
- copy() - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
-
Returns a copy of the statistic with the same internal state.
- copy(ResizableDoubleArray, ResizableDoubleArray) - Static method in class org.apache.commons.math.util.ResizableDoubleArray
-
Copies source to dest, copying the underlying data, so dest is
a new, independent copy of source.
- copy() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns a copy of the ResizableDoubleArray.
- copyArray(double[], double[]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Copy an array.
- copyArray(double[][], double[][]) - Static method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Copy an array.
- copyArray(double[], double[]) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
- copyBlockPart(T[], int, int, int, int, int, T[], int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Copy a part of a block into another one
- copyBlockPart(double[], int, int, int, int, int, double[], int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Copy a part of a block into another one
- copyIn(T[][]) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Replaces data with a fresh copy of the input array.
- copyIn(double[][]) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Replaces data with a fresh copy of the input array.
- copyIn(BigDecimal[][]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Replaces data with a fresh copy of the input array.
- copyIn(double[][]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Replaces data with a fresh copy of the input array.
- copyIn(String[][]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Replaces data with BigDecimals represented by the strings in the input
array.
- copyIn(double[][]) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Replaces data with a fresh copy of the input array.
- copyOf(double[], int) - Method in class org.apache.commons.math.optimization.direct.PowellOptimizer
-
Java 1.5 does not support Arrays.copyOf()
- copyOf(int[], int) - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Java 1.5 does not support Arrays.copyOf()
- copyOut() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns a fresh copy of the underlying data array.
- copyOut() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns a fresh copy of the underlying data array.
- copyOut() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a fresh copy of the underlying data array.
- copyOut() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns a fresh copy of the underlying data array.
- copysign(Dfp, Dfp) - Static method in class org.apache.commons.math.dfp.Dfp
-
Creates an instance that is the same as x except that it has the sign of y.
- copySign(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Returns the first argument with the sign of the second argument.
- copySign(float, float) - Static method in class org.apache.commons.math.util.FastMath
-
Returns the first argument with the sign of the second argument.
- copySubMatrix(int, int, int, int, T[][]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Copy a submatrix.
- copySubMatrix(int[], int[], T[][]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Copy a submatrix.
- copySubMatrix(int, int, int, int, double[][]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Copy a submatrix.
- copySubMatrix(int[], int[], double[][]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Copy a submatrix.
- copySubMatrix(int, int, int, int, T[][]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Copy a submatrix.
- copySubMatrix(int[], int[], T[][]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Copy a submatrix.
- copySubMatrix(int, int, int, int, double[][]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Copy a submatrix.
- copySubMatrix(int[], int[], double[][]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Copy a submatrix.
- CorrelatedRandomVectorGenerator - Class in org.apache.commons.math.random
-
- CorrelatedRandomVectorGenerator(double[], RealMatrix, double, NormalizedRandomGenerator) - Constructor for class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Simple constructor.
- CorrelatedRandomVectorGenerator(RealMatrix, double, NormalizedRandomGenerator) - Constructor for class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Simple constructor.
- correlation(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Computes the Pearson's product-moment correlation coefficient between the two arrays.
- correlation(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Computes the Spearman's rank correlation coefficient between the two arrays.
- correlationMatrix - Variable in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
correlation matrix
- COS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- cos() - Method in class org.apache.commons.math.complex.Complex
-
Compute the
cosine
of this complex number.
- cos(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the cosine of the argument.
- cos(double) - Static method in class org.apache.commons.math.util.FastMath
-
Cosine function
- cosAngle(RealVector, RealVector) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
-
Compute the cosine of the angle between 2 vectors.
- COSH - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- cosh() - Method in class org.apache.commons.math.complex.Complex
-
- cosh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the hyperbolic cosine of a number.
- cosh(double) - Static method in class org.apache.commons.math.util.MathUtils
-
- COSINE_TABLE_A - Static variable in class org.apache.commons.math.util.FastMath
-
Cosine table (high bits).
- COSINE_TABLE_B - Static variable in class org.apache.commons.math.util.FastMath
-
Cosine table (low bits).
- cosInternal(Dfp[]) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Computes cos(a) Used when 0 < a < pi/4.
- cosQ(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute cosine in the first quadrant by subtracting input from PI/2 and
then calling sinQ.
- cost - Variable in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Cost value (square root of the sum of the residuals).
- cost - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Cost value (square root of the sum of the residuals).
- costEvaluations - Variable in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Number of cost evaluations.
- costPerStep - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
overall cost of applying step reduction up to iteration k+1, in number of calls.
- costPerTimeUnit - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
cost per unit step.
- costRelativeTolerance - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Desired relative error in the sum of squares.
- costRelativeTolerance - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Desired relative error in the sum of squares.
- count - Variable in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Unidimensional counter.
- count - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Modifications count.
- count - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Modifications count.
- counter - Variable in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Multidimensional counter.
- Covariance - Class in org.apache.commons.math.stat.correlation
-
Computes covariances for pairs of arrays or columns of a matrix.
- Covariance() - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a Covariance with no data
- Covariance(double[][], boolean) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a Covariance matrix from a rectangular array
whose columns represent covariates.
- Covariance(double[][]) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a Covariance matrix from a rectangular array
whose columns represent covariates.
- Covariance(RealMatrix, boolean) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a covariance matrix from a matrix whose columns
represent covariates.
- Covariance(RealMatrix) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a covariance matrix from a matrix whose columns
represent covariates.
- covariance(double[], double[], boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Computes the covariance between the two arrays.
- covariance(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Computes the covariance between the two arrays, using the bias-corrected
formula.
- covarianceImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Covariance statistic implementation - cannot be reset.
- covarianceMatrix - Variable in class org.apache.commons.math.stat.correlation.Covariance
-
covariance matrix
- covarianceToCorrelation(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Derives a correlation matrix from a covariance matrix.
- createAdaptor(RandomGenerator) - Static method in class org.apache.commons.math.random.RandomAdaptor
-
Factory method to create a Random using the supplied
RandomGenerator.
- createArithmeticException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createArithmeticException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new ArithmeticException with specified formatted detail message.
- createArrayIndexOutOfBoundsException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createArrayIndexOutOfBoundsException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new ArrayIndexOutOfBoundsException with specified formatted detail message.
- createBigIdentityMatrix(int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBigMatrix(double[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBigMatrix(BigDecimal[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBigMatrix(BigDecimal[][], boolean) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBigMatrix(String[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBlocksLayout(Field<T>, int, int) - Static method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Create a data array in blocks layout.
- createBlocksLayout(int, int) - Static method in class org.apache.commons.math.linear.BlockRealMatrix
-
Create a data array in blocks layout.
- createChebyshevPolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Create a Chebyshev polynomial of the first kind.
- createColumnBigMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createColumnBigMatrix(BigDecimal[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createColumnBigMatrix(String[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createColumnFieldMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a column
FieldMatrix using the data from the input
array.
- createColumnRealMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a column
RealMatrix using the data from the input
array.
- createComplex(double, double) - Method in class org.apache.commons.math.complex.Complex
-
Create a complex number given the real and imaginary parts.
- createConcurrentModificationException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createConcurrentModificationException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new ConcurrentModificationException with specified formatted detail message.
- createContributingStatistics() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Creates and returns a SummaryStatistics whose data will be
aggregated with those of this AggregateSummaryStatistics.
- createEOFException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createEOFException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new EOFException with specified formatted detail message.
- createFieldDiagonalMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns a diagonal matrix with specified elements.
- createFieldIdentityMatrix(Field<T>, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns dimension x dimension identity matrix.
- createFieldMatrix(Field<T>, int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createFieldMatrix(T[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns a
FieldMatrix whose entries are the the values in the
the input array.
- createFieldVector(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a
FieldVector using the data from the input array.
- createHermitePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Create a Hermite polynomial.
- createIllegalArgumentException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createIllegalArgumentException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new IllegalArgumentException with specified formatted detail message.
- createIllegalArgumentException(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new IllegalArgumentException with specified nested
Throwable root cause.
- createIllegalStateException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createIllegalStateException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new IllegalStateException with specified formatted detail message.
- createInternalError(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Create an RuntimeException for an internal error.
- createIOException(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new IOException with specified nested
Throwable root cause.
- createLaguerrePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Create a Laguerre polynomial.
- createLegendrePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Create a Legendre polynomial.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createNoSuchElementException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createNoSuchElementException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new NoSuchElementException with specified formatted detail message.
- createNullPointerException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createNullPointerException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Deprecated.
in 2.2. Checks for "null" must not be performed in Commons-Math.
- createParametersGuesser(WeightedObservedPoint[]) - Method in class org.apache.commons.math.optimization.fitting.GaussianFitter
-
Factory method to create a GaussianParametersGuesser
instance initialized with the specified observations.
- createParseException(int, String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createParseException(int, Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new ParseException with specified
formatted detail message.
- createRealDiagonalMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns a diagonal matrix with specified elements.
- createRealIdentityMatrix(int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns dimension x dimension identity matrix.
- createRealMatrix(int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createRealMatrix(double[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns a
RealMatrix whose entries are the the values in the
the input array.
- createRealVector(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a
RealVector using the data from the input array.
- createRowBigMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createRowBigMatrix(BigDecimal[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createRowBigMatrix(String[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createRowFieldMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a row
FieldMatrix using the data from the input
array.
- createRowRealMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a row
RealMatrix using the data from the input
array.
- createTableau(boolean) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Create the tableau by itself.
- createUnsupportedOperationException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createWeightedObservedPointComparator() - Method in class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
-
Factory method creating Comparator for comparing
WeightedObservedPoint instances.
- crossover(Chromosome, Chromosome) - Method in interface org.apache.commons.math.genetics.CrossoverPolicy
-
Perform a crossover operation on the given chromosomes.
- crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math.genetics.OnePointCrossover
-
Performs one point crossover.
- crossover(AbstractListChromosome<T>, AbstractListChromosome<T>) - Method in class org.apache.commons.math.genetics.OnePointCrossover
-
- CrossoverPolicy - Interface in org.apache.commons.math.genetics
-
Policy used to create a pair of new chromosomes by performing a crossover
operation on a source pair of chromosomes.
- crossoverPolicy - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
-
the crossover policy used by the algorithm.
- crossoverRate - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
-
the rate of crossover for the algorithm.
- crossProduct(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
-
Compute the cross-product of two vectors.
- cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.AbstractDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(int, int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
For this distribution, X, this method returns P(X ≤ x).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.Distribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(double, double) - Method in interface org.apache.commons.math.distribution.Distribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
For this distribution, X, this method returns P(X ≤ x).
- cumulativeProbability(int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(int, int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
-
For this distribution, X, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
For this distribution, X, this method returns P(X ≤ x).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
The probability distribution function P(X <= x) for a Poisson
distribution.
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
The probability distribution function P(X <= x) for a Zipf distribution.
- current - Variable in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
-
- current - Variable in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
-
Current entry.
- current - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
-
Index of current element.
- current - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
-
Index of current element.
- currentDegree - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Degree of the interpolation polynoms.
- currentDerivative - Variable in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
-
Current derivative.
- currentState - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
current state
- CurveFitter - Class in org.apache.commons.math.optimization.fitting
-
Fitter for parametric univariate real functions y = f(x).
- CurveFitter(DifferentiableMultivariateVectorialOptimizer) - Constructor for class org.apache.commons.math.optimization.fitting.CurveFitter
-
Simple constructor.
- CurveFitter.TheoreticalValuesFunction - Class in org.apache.commons.math.optimization.fitting
-
Vectorial function computing function theoretical values.
- CurveFitter.TheoreticalValuesFunction(ParametricRealFunction) - Constructor for class org.apache.commons.math.optimization.fitting.CurveFitter.TheoreticalValuesFunction
-
Simple constructor.
- e - Variable in class org.apache.commons.math.dfp.DfpField
-
- E - Static variable in class org.apache.commons.math.util.FastMath
-
Napier's constant e, base of the natural logarithm.
- E1 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Error array, element 1.
- E1_01 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
First error weights array, element 1.
- E1_06 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
First error weights array, element 6.
- E1_07 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
First error weights array, element 7.
- E1_08 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
First error weights array, element 8.
- E1_09 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
First error weights array, element 9.
- E1_10 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
First error weights array, element 10.
- E1_11 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
First error weights array, element 11.
- E1_12 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
First error weights array, element 12.
- E2_01 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Second error weights array, element 1.
- E2_06 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Second error weights array, element 6.
- E2_07 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Second error weights array, element 7.
- E2_08 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Second error weights array, element 8.
- E2_09 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Second error weights array, element 9.
- E2_10 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Second error weights array, element 10.
- E2_11 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Second error weights array, element 11.
- E2_12 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Second error weights array, element 12.
- E3 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Error array, element 3.
- E4 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Error array, element 4.
- E5 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Error array, element 5.
- E6 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Error array, element 6.
- E7 - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Error array, element 7.
- ebeDivide(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Element-by-element division.
- ebeDivide(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Element-by-element division.
- ebeDivide(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Element-by-element division.
- ebeDivide(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Element-by-element division.
- ebeDivide(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Element-by-element division.
- ebeDivide(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Element-by-element division.
- ebeDivide(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Element-by-element division.
- ebeDivide(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Element-by-element division.
- ebeDivide(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Element-by-element division.
- ebeDivide(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Element-by-element division.
- ebeDivide(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Element-by-element division.
- ebeDivide(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Element-by-element division.
- ebeDivide(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Element-by-element division.
- ebeDivide(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Element-by-element division.
- ebeDivide(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Element-by-element division.
- ebeMultiply(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Element-by-element multiplication.
- ebeMultiply(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Element-by-element multiplication.
- ebeMultiply(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Element-by-element multiplication.
- ebeMultiply(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Element-by-element multiplication.
- ebeMultiply(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Element-by-element multiplication.
- ebeMultiply(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Element-by-element multiplication.
- ebeMultiply(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Element-by-element multiplication.
- ebeMultiply(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Element-by-element multiplication.
- ebeMultiply(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Element-by-element multiplication.
- ebeMultiply(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Element-by-element multiplication.
- ebeMultiply(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Element-by-element multiplication.
- ebeMultiply(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Element-by-element multiplication.
- ebeMultiply(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Element-by-element multiplication.
- ebeMultiply(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Element-by-element multiplication.
- ebeMultiply(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Element-by-element multiplication.
- eDA - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Stored data values
- EigenDecomposition - Interface in org.apache.commons.math.linear
-
An interface to classes that implement an algorithm to calculate the
eigen decomposition of a real matrix.
- eigenDecomposition - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Eigen decomposition of the tridiagonal matrix.
- EigenDecompositionImpl - Class in org.apache.commons.math.linear
-
Calculates the eigen decomposition of a real symmetric
matrix.
- EigenDecompositionImpl(RealMatrix, double) - Constructor for class org.apache.commons.math.linear.EigenDecompositionImpl
-
Calculates the eigen decomposition of the given symmetric matrix.
- EigenDecompositionImpl(double[], double[], double) - Constructor for class org.apache.commons.math.linear.EigenDecompositionImpl
-
Calculates the eigen decomposition of the symmetric tridiagonal
matrix.
- EigenDecompositionImpl.Solver - Class in org.apache.commons.math.linear
-
Specialized solver.
- EigenDecompositionImpl.Solver(double[], double[], ArrayRealVector[]) - Constructor for class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
-
Build a solver from decomposed matrix.
- eigenvectors - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Eigenvectors.
- eigenvectors - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
-
Eigenvectors.
- EIGHTHS - Static variable in class org.apache.commons.math.util.FastMath
-
Eighths.
- elitismRate - Variable in class org.apache.commons.math.genetics.ElitisticListPopulation
-
percentage of chromosomes copied to the next generation
- ElitisticListPopulation - Class in org.apache.commons.math.genetics
-
Population of chromosomes which uses elitism (certain percentace of the best
chromosomes is directly copied to the next generation).
- ElitisticListPopulation(List<Chromosome>, int, double) - Constructor for class org.apache.commons.math.genetics.ElitisticListPopulation
-
Creates a new ElitisticListPopulation instance.
- ElitisticListPopulation(int, double) - Constructor for class org.apache.commons.math.genetics.ElitisticListPopulation
-
Creates a new ListPopulation instance and initializes its inner
chromosome list.
- EmbeddedRungeKuttaIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements the common part of all embedded Runge-Kutta
integrators for Ordinary Differential Equations.
- EmbeddedRungeKuttaIntegrator(String, boolean, double[], double[][], double[], RungeKuttaStepInterpolator, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Build a Runge-Kutta integrator with the given Butcher array.
- EmbeddedRungeKuttaIntegrator(String, boolean, double[], double[][], double[], RungeKuttaStepInterpolator, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Build a Runge-Kutta integrator with the given Butcher array.
- EmpiricalDistribution - Interface in org.apache.commons.math.random
-
Represents an
empirical probability distribution -- a probability distribution derived
from observed data without making any assumptions about the functional form
of the population distribution that the data come from.
- empiricalDistribution - Variable in class org.apache.commons.math.random.ValueServer
-
Empirical probability distribution for use with DIGEST_MODE.
- EmpiricalDistributionImpl - Class in org.apache.commons.math.random
-
Implements EmpiricalDistribution interface.
- EmpiricalDistributionImpl() - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Creates a new EmpiricalDistribution with the default bin count.
- EmpiricalDistributionImpl(int) - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Creates a new EmpiricalDistribution with the specified bin count.
- EmpiricalDistributionImpl.ArrayDataAdapter - Class in org.apache.commons.math.random
-
DataAdapter for data provided as array of doubles.
- EmpiricalDistributionImpl.ArrayDataAdapter(double[]) - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
-
Construct an ArrayDataAdapter from a double[] array
- EmpiricalDistributionImpl.DataAdapter - Class in org.apache.commons.math.random
-
Provides methods for computing sampleStats and
beanStats abstracting the source of data.
- EmpiricalDistributionImpl.DataAdapter() - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapter
-
- EmpiricalDistributionImpl.DataAdapterFactory - Class in org.apache.commons.math.random
-
Factory of DataAdapter objects.
- EmpiricalDistributionImpl.DataAdapterFactory() - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapterFactory
-
- EmpiricalDistributionImpl.StreamDataAdapter - Class in org.apache.commons.math.random
-
DataAdapter for data provided through some input stream
- EmpiricalDistributionImpl.StreamDataAdapter(BufferedReader) - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
-
Create a StreamDataAdapter from a BufferedReader
- emptyStrategy - Variable in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Selected strategy for empty clusters.
- end() - Method in class org.apache.commons.math.linear.DefaultFieldMatrixChangingVisitor
-
End visiting a matrix.
- end() - Method in class org.apache.commons.math.linear.DefaultFieldMatrixPreservingVisitor
-
End visiting a matrix.
- end() - Method in class org.apache.commons.math.linear.DefaultRealMatrixChangingVisitor
-
End visiting a matrix.
- end() - Method in class org.apache.commons.math.linear.DefaultRealMatrixPreservingVisitor
-
End visiting a matrix.
- end() - Method in interface org.apache.commons.math.linear.FieldMatrixChangingVisitor
-
End visiting a matrix.
- end() - Method in interface org.apache.commons.math.linear.FieldMatrixPreservingVisitor
-
End visiting a matrix.
- end() - Method in interface org.apache.commons.math.linear.RealMatrixChangingVisitor
-
End visiting a matrix.
- end() - Method in interface org.apache.commons.math.linear.RealMatrixPreservingVisitor
-
End visiting a matrix.
- end() - Method in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
-
End visiting the Nordsieck vector.
- endTime - Variable in class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
-
Deprecated.
Desired end time.
- entries - Variable in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Storage for (sparse) matrix elements.
- entries - Variable in class org.apache.commons.math.linear.OpenMapRealVector
-
Entries of the vector.
- entries - Variable in class org.apache.commons.math.linear.SparseFieldMatrix
-
Storage for (sparse) matrix elements.
- entries - Variable in class org.apache.commons.math.linear.SparseFieldVector
-
Entries of the vector.
- EPS_MIN - Static variable in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Tolerance to avoid division by zero.
- epsilon - Variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Convergence criterion for cumulative probability.
- epsilon - Variable in class org.apache.commons.math.linear.OpenMapRealVector
-
Tolerance for having a value considered zero.
- epsilon - Variable in class org.apache.commons.math.optimization.linear.SimplexSolver
-
Amount of error to accept in floating point comparisons.
- epsilon - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Amount of error to accept in floating point comparisons.
- EPSILON - Static variable in class org.apache.commons.math.util.MathUtils
-
Smallest positive number such that 1 - EPSILON is not numerically equal to 1.
- equals(Object) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
- equals(Object) - Method in class org.apache.commons.math.complex.Complex
-
Test for the equality of two Complex objects.
- equals(Object) - Method in class org.apache.commons.math.dfp.Dfp
-
Check if instance is equal to x.
- equals(Object) - Method in class org.apache.commons.math.fraction.BigFraction
-
Test for the equality of two fractions.
- equals(Object) - Method in class org.apache.commons.math.fraction.Fraction
-
Test for the equality of two fractions.
- equals(Object) - Method in class org.apache.commons.math.geometry.Vector3D
-
Test for the equality of two 3D vectors.
- equals(Object) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns true iff object is a
FieldMatrix instance with the same dimensions as this
and all corresponding matrix entries are equal.
- equals(Object) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns true iff object is a
RealMatrix instance with the same dimensions as this
and all corresponding matrix entries are equal.
- equals(Object) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Test for the equality of two real vectors.
- equals(Object) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Test for the equality of two real vectors.
- equals(Object) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns true iff object is a
BigMatrixImpl instance with the same dimensions as this
and all corresponding matrix entries are equal.
- equals(Object) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Implementation Note: This performs an exact comparison, and as a result
it is possible for a.subtract(b} to be the zero vector, while
a.equals(b) == false.
- equals(Object) - Method in class org.apache.commons.math.linear.SparseFieldVector
- equals(Object) - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
- equals(Object) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
- equals(Object) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
- equals(Object) - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
Returns true iff object is an
AbstractStorelessUnivariateStatistic returning the same
values as this for getResult() and getN()
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
-
Returns true iff object is a
SummaryStatistics instance and all statistics have the
same values as this.
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns true iff object is a MultivariateSummaryStatistics
instance and all statistics have the same values as this.
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
Returns true iff object is a
StatisticalSummaryValues instance and all statistics have
the same values as this.
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns true iff object is a
SummaryStatistics instance and all statistics have the
same values as this.
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns true iff object is a MultivariateSummaryStatistics
instance and all statistics have the same values as this.
- equals(Object) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns true iff object is a
SummaryStatistics instance and all statistics have the
same values as this.
- equals(Object) - Method in class org.apache.commons.math.stat.Frequency
- equals(Object) - Method in class org.apache.commons.math.util.BigReal
- equals(Object) - Method in class org.apache.commons.math.util.DefaultTransformer
- equals(float, float) - Static method in class org.apache.commons.math.util.MathUtils
-
Deprecated.
as of 2.2 his method considers that NaN == NaN. In release
3.0, the semantics will change in order to comply with IEEE754 where it
is specified that NaN != NaN.
New methods have been added for those cases wher the old semantics is
useful (see e.g. equalsIncludingNaN.
- equals(float, float, float) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true if both arguments are equal or within the range of allowed
error (inclusive).
- equals(float, float, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true if both arguments are equal or within the range of allowed
error (inclusive).
- equals(float[], float[]) - Static method in class org.apache.commons.math.util.MathUtils
-
Deprecated.
as of 2.2 this method considers that NaN == NaN. In release
3.0, the semantics will change in order to comply with IEEE754 where it
is specified that NaN != NaN.
New methods have been added for those cases where the old semantics is
useful (see e.g. equalsIncludingNaN.
- equals(double, double) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true iff both arguments are NaN or neither is NaN and they are
equal
- equals(double, double, double) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true if both arguments are equal or within the range of allowed
error (inclusive).
- equals(double, double, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true if both arguments are equal or within the range of allowed
error (inclusive).
- equals(double[], double[]) - Static method in class org.apache.commons.math.util.MathUtils
-
- equals(Object) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns true iff object is a ResizableDoubleArray with the same properties
as this and an identical internal storage array.
- equals(Object) - Method in class org.apache.commons.math.util.TransformerMap
- equalsIncludingNaN(float, float) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true if both arguments are NaN or neither is NaN and they are
equal as defined by
equals(x, y, 1).
- equalsIncludingNaN(float, float, float) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true if both arguments are NaN or are equal or within the range
of allowed error (inclusive).
- equalsIncludingNaN(float, float, int) - Static method in class org.apache.commons.math.util.MathUtils
-
- equalsIncludingNaN(float[], float[]) - Static method in class org.apache.commons.math.util.MathUtils
-
- equalsIncludingNaN(double, double) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true if both arguments are NaN or neither is NaN and they are
equal as defined by
equals(x, y, 1).
- equalsIncludingNaN(double, double, double) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns true if both arguments are NaN or are equal or within the range
of allowed error (inclusive).
- equalsIncludingNaN(double, double, int) - Static method in class org.apache.commons.math.util.MathUtils
-
- equalsIncludingNaN(double[], double[]) - Static method in class org.apache.commons.math.util.MathUtils
-
- equations - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Differential equations to integrate.
- equations - Variable in class org.apache.commons.math.ode.FirstOrderConverter
-
Underlying second order equations set.
- Erf - Class in org.apache.commons.math.special
-
This is a utility class that provides computation methods related to the
error functions.
- Erf() - Constructor for class org.apache.commons.math.special.Erf
-
Default constructor.
- erf(double) - Static method in class org.apache.commons.math.special.Erf
-
Returns the error function
- erfc(double) - Static method in class org.apache.commons.math.special.Erf
-
Returns the complementary error function
- ERR_SCALE - Static variable in class org.apache.commons.math.dfp.Dfp
-
The amount under/overflows are scaled by before going to trap handler
- errfac - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Error coefficients for the interpolation.
- eSplit - Variable in class org.apache.commons.math.dfp.DfpField
-
A two elements
Dfp array with value e split in two pieces.
- estimate(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Solve an estimation problem.
- estimate - Variable in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Current value of the parameter
- estimate(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
-
Deprecated.
Solve an estimation problem.
- estimate(EstimationProblem) - Method in class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Solve an estimation problem using a least squares criterion.
- estimate(EstimationProblem) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Solve an estimation problem using the Levenberg-Marquardt algorithm.
- EstimatedParameter - Class in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- EstimatedParameter(String, double) - Constructor for class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Simple constructor.
- EstimatedParameter(String, double, boolean) - Constructor for class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Simple constructor.
- EstimatedParameter(EstimatedParameter) - Constructor for class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Copy constructor.
- estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Compute the error ratio.
- estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Compute the error ratio.
- estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Compute the error ratio.
- estimateError(double[]) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Estimate interpolation error.
- estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
-
Compute the error ratio.
- estimateErrorVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Estimates the variance of the error.
- estimateRegressandVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Returns the variance of the regressand, ie Var(y).
- estimateRegressandVariance() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
-
Returns the variance of the regressand, ie Var(y).
- estimateRegressionParameters() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Estimates the regression parameters b.
- estimateRegressionParameters() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
-
Estimates the regression parameters b.
- estimateRegressionParametersStandardErrors() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Returns the standard errors of the regression parameters.
- estimateRegressionParametersStandardErrors() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
-
Returns the standard errors of the regression parameters.
- estimateRegressionParametersVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Estimates the variance of the regression parameters, ie Var(b).
- estimateRegressionParametersVariance() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
-
Estimates the variance of the regression parameters, ie Var(b).
- estimateRegressionStandardError() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Estimates the standard error of the regression.
- estimateResiduals() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Estimates the residuals, ie u = y - X*b.
- estimateResiduals() - Method in interface org.apache.commons.math.stat.regression.MultipleLinearRegression
-
Estimates the residuals, ie u = y - X*b.
- EstimationException - Exception in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- EstimationException(String, Object...) - Constructor for exception org.apache.commons.math.estimation.EstimationException
-
Deprecated.
Simple constructor.
- EstimationException(Localizable, Object...) - Constructor for exception org.apache.commons.math.estimation.EstimationException
-
Deprecated.
Simple constructor.
- EstimationProblem - Interface in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- Estimator - Interface in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- eString - Static variable in class org.apache.commons.math.dfp.DfpField
-
High precision string representation of e.
- EuclideanIntegerPoint - Class in org.apache.commons.math.stat.clustering
-
A simple implementation of
Clusterable for points with integer coordinates.
- EuclideanIntegerPoint(int[]) - Constructor for class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
-
Build an instance wrapping an integer array.
- EulerIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements a simple Euler integrator for Ordinary
Differential Equations.
- EulerIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.EulerIntegrator
-
Simple constructor.
- EulerStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements a linear interpolator for step.
- EulerStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
-
Simple constructor.
- EulerStepInterpolator(EulerStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
-
Copy constructor.
- eval(UnivariateRealFunction, double) - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- evaluate(double[], double) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Uses Horner's Method to evaluate the polynomial with the given coefficients at
the argument.
- evaluate(double[], double[], double) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
- evaluate(double[], double[], double) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Evaluate the Newton polynomial using nested multiplication.
- evaluate(double[]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Evaluate the objective function on one point.
- evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
- evaluate() - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Returns the result of evaluating the statistic over the stored data.
- evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Returns the result of evaluating the statistic over the input array.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Returns the result of evaluating the statistic over the specified entries
in the input array.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns the geometric mean of the entries in the specified portion
of the input array.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Returns the kurtosis of the entries in the specified portion of the
input array.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns the arithmetic mean of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns the weighted arithmetic mean of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns the weighted arithmetic mean of the entries in the input array.
- evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
This method calculates
SemiVariance for the entire array against the mean, using
instance properties varianceDirection and biasCorrection.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns the
SemiVariance of the designated values against the mean, using
instance properties varianceDirection and biasCorrection.
- evaluate(double[], SemiVariance.Direction) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
This method calculates
SemiVariance for the entire array against the mean, using
the current value of the biasCorrection instance property.
- evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns the
SemiVariance of the designated values against the cutoff, using
instance properties variancDirection and biasCorrection.
- evaluate(double[], double, SemiVariance.Direction) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns the
SemiVariance of the designated values against the cutoff in the
given direction, using the current value of the biasCorrection instance property.
- evaluate(double[], double, SemiVariance.Direction, boolean, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns the
SemiVariance of the designated values against the cutoff
in the given direction with the provided bias correction.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Returns the Skewness of the entries in the specifed portion of the
input array.
- evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns the Standard Deviation of the entries in the input array, or
Double.NaN if the array is empty.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns the Standard Deviation of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns the Standard Deviation of the entries in the specified portion of
the input array, using the precomputed mean value.
- evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns the Standard Deviation of the entries in the input array, using
the precomputed mean value.
- evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the variance of the entries in the input array, or
Double.NaN if the array is empty.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the variance of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the weighted variance of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the weighted variance of the entries in the the input array.
- evaluate(double[], double, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the variance of the entries in the specified portion of
the input array, using the precomputed mean value.
- evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the variance of the entries in the input array, using the
precomputed mean value.
- evaluate(double[], double[], double, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the weighted variance of the entries in the specified portion of
the input array, using the precomputed weighted mean value.
- evaluate(double[], double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the weighted variance of the values in the input array, using
the precomputed weighted mean value.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Returns the maximum of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Returns the minimum of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Returns the result of evaluating the statistic over the stored data.
- evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Returns an estimate of the pth percentile of the values
in the values array.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Returns an estimate of the quantileth percentile of the
designated values in the values array.
- evaluate(double[], int, int, double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Returns an estimate of the pth percentile of the values
in the values array, starting with the element in (0-based)
position begin in the array and including length
values.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns the product of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns the weighted product of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double[]) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns the weighted product of the entries in the input array.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
The sum of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
The weighted sum of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], double[]) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
The weighted sum of the entries in the the input array.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Returns the sum of the natural logs of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Returns the sum of the squares of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- evaluate(double[]) - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
-
Returns the result of evaluating the statistic over the input array.
- evaluate(double[], int, int) - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
-
Returns the result of evaluating the statistic over the specified entries
in the input array.
- evaluate(double[], double[]) - Method in interface org.apache.commons.math.stat.descriptive.WeightedEvaluation
-
Returns the result of evaluating the statistic over the input array,
using the supplied weights.
- evaluate(double[], double[], int, int) - Method in interface org.apache.commons.math.stat.descriptive.WeightedEvaluation
-
Returns the result of evaluating the statistic over the specified entries
in the input array, using corresponding entries in the supplied weights array.
- evaluate(double) - Method in class org.apache.commons.math.util.ContinuedFraction
-
Evaluates the continued fraction at the value x.
- evaluate(double, double) - Method in class org.apache.commons.math.util.ContinuedFraction
-
Evaluates the continued fraction at the value x.
- evaluate(double, int) - Method in class org.apache.commons.math.util.ContinuedFraction
-
Evaluates the continued fraction at the value x.
- evaluate(double, double, int) - Method in class org.apache.commons.math.util.ContinuedFraction
-
Evaluates the continued fraction at the value x.
- evaluateNewSimplex(RealPointValuePair[], double, Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.MultiDirectional
-
Compute and evaluate a new simplex.
- evaluateSimplex(Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Evaluate all the non-evaluated points of the simplex.
- evaluateStep(StepInterpolator) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Evaluate the impact of the proposed step on all managed
event handlers.
- evaluateStep(StepInterpolator) - Method in class org.apache.commons.math.ode.events.EventState
-
Evaluate the impact of the proposed step on the event handler.
- evaluations - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Number of evaluations already performed.
- evaluations - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Number of evaluations already performed.
- evaluations - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Number of evaluations already performed.
- evaluations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Number of evaluations already performed.
- evaluations - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Number of evaluations already performed.
- evaluations - Variable in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Number of function evaluations.
- even - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Parity of the permutation associated with the LU decomposition
- even - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
-
Parity of the permutation associated with the LU decomposition
- EventException - Exception in org.apache.commons.math.ode.events
-
This exception is made available to users to report
the error conditions that are triggered by
EventHandler
- EventException(String, Object...) - Constructor for exception org.apache.commons.math.ode.events.EventException
-
- EventException(Localizable, Object...) - Constructor for exception org.apache.commons.math.ode.events.EventException
-
Simple constructor.
- EventException(Throwable) - Constructor for exception org.apache.commons.math.ode.events.EventException
-
Create an exception with a given root cause.
- eventException - Variable in exception org.apache.commons.math.ode.events.EventState.EmbeddedEventException
-
Embedded exception.
- EventHandler - Interface in org.apache.commons.math.ode.events
-
This interface represents a handler for discrete events triggered
during ODE integration.
- EventHandlerWithJacobians - Interface in org.apache.commons.math.ode.jacobians
-
Deprecated.
as of 2.2 the complete package is deprecated, it will be replaced
in 3.0 by a completely rewritten implementation
- eventOccurred(double, double[], boolean) - Method in class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
-
Deprecated.
Handle an event and choose what to do next.
- eventOccurred(double, double[], boolean) - Method in interface org.apache.commons.math.ode.events.EventHandler
-
Handle an event and choose what to do next.
- eventOccurred(double, double[], double[][], double[][], boolean) - Method in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
-
Deprecated.
Handle an event and choose what to do next.
- eventOccurred(double, double[], boolean) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
-
Deprecated.
Handle an event and choose what to do next.
- eventsStates - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Events states.
- EventState - Class in org.apache.commons.math.ode.events
-
This class handles the state for one
event handler during integration steps.
- EventState(EventHandler, double, double, int) - Constructor for class org.apache.commons.math.ode.events.EventState
-
Simple constructor.
- EventState.EmbeddedDerivativeException - Exception in org.apache.commons.math.ode.events
-
Local exception for embedding DerivativeException.
- EventState.EmbeddedDerivativeException(DerivativeException) - Constructor for exception org.apache.commons.math.ode.events.EventState.EmbeddedDerivativeException
-
Simple constructor.
- EventState.EmbeddedEventException - Exception in org.apache.commons.math.ode.events
-
Local exception for embedding EventException.
- EventState.EmbeddedEventException(EventException) - Constructor for exception org.apache.commons.math.ode.events.EventState.EmbeddedEventException
-
Simple constructor.
- evolve(Population, StoppingCondition) - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Evolve the given population.
- EXACT_STIRLING_ERRORS - Static variable in class org.apache.commons.math.distribution.SaddlePointExpansion
-
exact Stirling expansion error for certain values.
- EXP - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- exp() - Method in class org.apache.commons.math.complex.Complex
-
- exp - Variable in class org.apache.commons.math.dfp.Dfp
-
Exponent.
- exp(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Computes e to the given power.
- exp - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
Stepsize control exponent.
- exp - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Stepsize control exponent.
- exp(double) - Static method in class org.apache.commons.math.util.FastMath
-
Exponential function.
- exp(double, double, double[]) - Static method in class org.apache.commons.math.util.FastMath
-
Internal helper method for exponential function.
- EXP_FRAC_TABLE_A - Static variable in class org.apache.commons.math.util.FastMath
-
Exponential over the range of 0 - 1 in increments of 2^-10
exp(x/1024) = expFracTableA[x] + expFracTableB[x].
- EXP_FRAC_TABLE_B - Static variable in class org.apache.commons.math.util.FastMath
-
Exponential over the range of 0 - 1 in increments of 2^-10
exp(x/1024) = expFracTableA[x] + expFracTableB[x].
- EXP_INT_TABLE_A - Static variable in class org.apache.commons.math.util.FastMath
-
Exponential evaluated at integer values,
exp(x) = expIntTableA[x + 750] + expIntTableB[x+750].
- EXP_INT_TABLE_B - Static variable in class org.apache.commons.math.util.FastMath
-
Exponential evaluated at integer values,
exp(x) = expIntTableA[x + 750] + expIntTableB[x+750]
- expand() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Expands the internal storage array using the expansion factor.
- expandTo(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Expands the internal storage array to the specified size.
- expansionFactor - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
The expansion factor of the array.
- expansionMode - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
Determines whether array expansion by expansionFactor
is additive or multiplicative.
- expint(int, double[]) - Static method in class org.apache.commons.math.util.FastMath
-
Compute exp(p) for a integer p in extended precision.
- expInternal(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Computes e to the given power.
- EXPM1 - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- expm1(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute exp(x) - 1
- expm1(double, double[]) - Static method in class org.apache.commons.math.util.FastMath
-
Internal helper method for expm1
- exponent - Variable in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Exponent parameter of the distribution.
- EXPONENTIAL_MODE - Static variable in class org.apache.commons.math.random.ValueServer
-
Exponential random deviates with mean = μ.
- ExponentialDistribution - Interface in org.apache.commons.math.distribution
-
The Exponential Distribution.
- ExponentialDistributionImpl - Class in org.apache.commons.math.distribution
-
- ExponentialDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Create a exponential distribution with the given mean.
- ExponentialDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Create a exponential distribution with the given mean.
- ExtendedFirstOrderDifferentialEquations - Interface in org.apache.commons.math.ode
-
This interface represents a first order differential equations set
with a main set of equations and an extension set.
- extractField(T[][]) - Static method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Get the elements type from an array.
- extractField(T[]) - Static method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Get the elements type from an array.
- extrapolate(int, int, double[][], double[]) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Extrapolate a vector.
- g(double, double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator.EndTimeChecker
-
Deprecated.
Compute the value of the switching function.
- g(double, double[]) - Method in interface org.apache.commons.math.ode.events.EventHandler
-
Compute the value of the switching function.
- g(double, double[], double[][], double[][]) - Method in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
-
Deprecated.
Compute the value of the switching function.
- g(double, double[]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
-
Deprecated.
Compute the value of the switching function.
- g0 - Variable in class org.apache.commons.math.ode.events.EventState
-
Value of the events handler at the beginning of the step.
- g0Positive - Variable in class org.apache.commons.math.ode.events.EventState
-
Simulated sign of g0 (we cheat when crossing events).
- gamma - Variable in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Internal Gamma distribution.
- gamma - Variable in class org.apache.commons.math.optimization.direct.MultiDirectional
-
Contraction coefficient.
- gamma - Variable in class org.apache.commons.math.optimization.direct.NelderMead
-
Contraction coefficient.
- Gamma - Class in org.apache.commons.math.special
-
This is a utility class that provides computation methods related to the
Gamma family of functions.
- Gamma() - Constructor for class org.apache.commons.math.special.Gamma
-
Default constructor.
- GAMMA - Static variable in class org.apache.commons.math.special.Gamma
-
- GammaDistribution - Interface in org.apache.commons.math.distribution
-
The Gamma Distribution.
- GammaDistributionImpl - Class in org.apache.commons.math.distribution
-
- GammaDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.GammaDistributionImpl
-
Create a new gamma distribution with the given alpha and beta values.
- GammaDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.GammaDistributionImpl
-
Create a new gamma distribution with the given alpha and beta values.
- GAUSSIAN_MODE - Static variable in class org.apache.commons.math.random.ValueServer
-
Gaussian random deviates with mean = μ, std dev = σ.
- GaussianDerivativeFunction - Class in org.apache.commons.math.optimization.fitting
-
- GaussianDerivativeFunction(double, double, double) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianDerivativeFunction
-
Constructs an instance with the specified parameters.
- GaussianDerivativeFunction(double[]) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianDerivativeFunction
-
Constructs an instance with the specified parameters.
- GaussianFitter - Class in org.apache.commons.math.optimization.fitting
-
- GaussianFitter(DifferentiableMultivariateVectorialOptimizer) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianFitter
-
Constructs an instance using the specified optimizer.
- GaussianFunction - Class in org.apache.commons.math.optimization.fitting
-
A Gaussian function.
- GaussianFunction(double, double, double, double) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Constructs an instance with the specified parameters.
- GaussianFunction(double[]) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Constructs an instance with the specified parameters.
- GaussianParametersGuesser - Class in org.apache.commons.math.optimization.fitting
-
- GaussianParametersGuesser(WeightedObservedPoint[]) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
-
Constructs instance with the specified observed points.
- GaussianRandomGenerator - Class in org.apache.commons.math.random
-
This class is a gaussian normalized random generator for scalars.
- GaussianRandomGenerator(RandomGenerator) - Constructor for class org.apache.commons.math.random.GaussianRandomGenerator
-
Create a new generator.
- GaussNewtonEstimator - Class in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- GaussNewtonEstimator() - Constructor for class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Simple constructor with default settings.
- GaussNewtonEstimator(int, double, double) - Constructor for class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Simple constructor.
- GaussNewtonOptimizer - Class in org.apache.commons.math.optimization.general
-
Gauss-Newton least-squares solver.
- GaussNewtonOptimizer(boolean) - Constructor for class org.apache.commons.math.optimization.general.GaussNewtonOptimizer
-
Simple constructor with default settings.
- gcd(int, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Gets the greatest common divisor of the absolute value of two numbers,
using the "binary gcd" method which avoids division and modulo
operations.
- gcd(long, long) - Static method in class org.apache.commons.math.util.MathUtils
-
Gets the greatest common divisor of the absolute value of two numbers,
using the "binary gcd" method which avoids division and modulo
operations.
- general - Variable in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Pattern used to build the message (general problem description).
- general - Variable in exception org.apache.commons.math.exception.MathIllegalStateException
-
Pattern used to build the message (general problem description).
- generalizedHarmonic(int, double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Calculates the Nth generalized harmonic number.
- generate(int) - Method in interface org.apache.commons.math.analysis.polynomials.PolynomialsUtils.RecurrenceCoefficientsGenerator
-
Generate recurrence coefficients.
- generationsEvolved - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
-
- generator - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Random generator for multi-start.
- generator - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Random generator for multi-start.
- generator - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Random generator for multi-start.
- generator - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Random generator for multi-start.
- generator - Variable in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Underlying generator.
- generator - Variable in class org.apache.commons.math.random.GaussianRandomGenerator
-
Underlying generator.
- generator - Variable in class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
-
Underlying scalar generator.
- generator - Variable in class org.apache.commons.math.random.UniformRandomGenerator
-
Underlying generator.
- GeneticAlgorithm - Class in org.apache.commons.math.genetics
-
Implementation of a genetic algorithm.
- GeneticAlgorithm(CrossoverPolicy, double, MutationPolicy, double, SelectionPolicy) - Constructor for class org.apache.commons.math.genetics.GeneticAlgorithm
-
- geoMean - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
geoMean of values that have been added
- geoMeanImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Geometric mean statistic implementation - can be reset by setter.
- geoMeanImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Geometric mean statistic implementation - can be reset by setter.
- GEOMETRIC_MEAN - Static variable in class org.apache.commons.math.stat.StatUtils
-
geometric mean
- GeometricMean - Class in org.apache.commons.math.stat.descriptive.moment
-
- GeometricMean() - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Create a GeometricMean instance
- GeometricMean(GeometricMean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Copy constructor, creates a new GeometricMean identical
to the original
- GeometricMean(SumOfLogs) - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Create a GeometricMean instance using the given SumOfLogs instance
- geometricMean(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the geometric mean of the entries in the input array, or
Double.NaN if the array is empty.
- geometricMean(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the geometric mean of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- geometricMeanImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Geometric mean statistic implementation - can be reset by setter.
- get(int...) - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
-
Get a matrix element.
- get(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Get the stored value associated with the given key
- get(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Get the stored value associated with the given key
- getA() - Method in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Gets a parameter value.
- getA(int, double) - Method in class org.apache.commons.math.util.ContinuedFraction
-
Access the n-th a coefficient of the continued fraction.
- getA1() - Method in class org.apache.commons.math.geometry.RotationOrder
-
Get the axis of the first rotation.
- getA2() - Method in class org.apache.commons.math.geometry.RotationOrder
-
Get the axis of the second rotation.
- getA3() - Method in class org.apache.commons.math.geometry.RotationOrder
-
Get the axis of the second rotation.
- getAbsoluteAccuracy() - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Get the actual absolute accuracy.
- getAbsoluteAccuracy() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Get the actual absolute accuracy.
- getAbsoluteAccuracy() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the actual absolute accuracy.
- getAdapter(Object) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl.DataAdapterFactory
-
Creates a DataAdapter from a data object
- getAllParameters() - Method in interface org.apache.commons.math.estimation.EstimationProblem
-
Deprecated.
Get all the parameters of the problem.
- getAllParameters() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Get all the parameters of the problem.
- getAlpha() - Method in interface org.apache.commons.math.distribution.BetaDistribution
-
Access the shape parameter, alpha
- getAlpha() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the shape parameter, alpha
- getAlpha() - Method in interface org.apache.commons.math.distribution.GammaDistribution
-
Access the shape parameter, alpha
- getAlpha() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the shape parameter, alpha
- getAlpha() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the azimuth of the vector.
- getAmplitude() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
-
Get the amplitude a.
- getAngle() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the angle of the rotation.
- getAngles(RotationOrder) - Method in class org.apache.commons.math.geometry.Rotation
-
Get the Cardan or Euler angles corresponding to the instance.
- getArgument() - Method in class org.apache.commons.math.complex.Complex
-
Compute the argument of this complex number.
- getArgument() - Method in exception org.apache.commons.math.exception.MathIllegalNumberException
-
- getArgument() - Method in exception org.apache.commons.math.FunctionEvaluationException
-
Returns the function argument that caused this exception.
- getArguments() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in exception org.apache.commons.math.MathException
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the arguments used to build the message of this throwable.
- getArity() - Method in class org.apache.commons.math.genetics.TournamentSelection
-
Gets the arity (number of chromosomes drawn to the tournament).
- getArray() - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
-
Get the underlying storage array
- getArtificialVariableOffset() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the offset of the first artificial variable.
- getAvailableLocales() - Static method in class org.apache.commons.math.complex.ComplexFormat
-
Get the set of locales for which complex formats are available.
- getAvailableLocales() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Get the set of locales for which complex formats are available.
- getAvailableLocales() - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Get the set of locales for which complex formats are available.
- getAvailableLocales() - Static method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the set of locales for which 3D vectors formats are available.
- getAvailableLocales() - Static method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the set of locales for which real vectors formats are available.
- getAxis() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the normalized axis of the rotation.
- getB() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Returns the bi-diagonal matrix B of the transform.
- getB() - Method in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Gets b parameter value.
- getB(int, double) - Method in class org.apache.commons.math.util.ContinuedFraction
-
Access the n-th b coefficient of the continued fraction.
- getBasicRow(int) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Checks whether the given column is basic.
- getBeta() - Method in interface org.apache.commons.math.distribution.BetaDistribution
-
Access the shape parameter, beta
- getBeta() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the shape parameter, beta
- getBeta() - Method in interface org.apache.commons.math.distribution.GammaDistribution
-
Access the scale parameter, beta
- getBeta() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the scale parameter, beta
- getBinCount() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Returns the number of bins.
- getBinCount() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Returns the number of bins.
- getBinStats() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Returns a list of
SummaryStatistics
containing statistics describing the values in each of the bins.
- getBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Returns a List of
SummaryStatistics instances containing
statistics describing the values in each of the bins.
- getBoundIsAllowed() - Method in exception org.apache.commons.math.exception.NumberIsTooLargeException
-
- getBoundIsAllowed() - Method in exception org.apache.commons.math.exception.NumberIsTooSmallException
-
- getC() - Method in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Gets c parameter value.
- getCenter() - Method in class org.apache.commons.math.stat.clustering.Cluster
-
Get the point chosen to be the center of this cluster.
- getCenters() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Returns a copy of the centers array.
- getChiSquare(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the Chi-Square value.
- getChiSquare() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get a Chi-Square-like value assuming the N residuals follow N
distinct normal distributions centered on 0 and whose variances are
the reciprocal of the weights.
- getChiSquareTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0
- getChromosomes() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Access the list of chromosomes.
- getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Returns a copy of the coefficients array.
- getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Returns a copy of the coefficients array.
- getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Returns a copy of the coefficients array.
- getCoefficients() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
-
Get the coefficients of the constraint (left hand side).
- getCoefficients() - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Get the coefficients of the linear equation being optimized.
- getColumn(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in column number col as an array.
- getColumn(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in column number col as an array.
- getColumn(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in column number col as an array.
- getColumn(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in column number col as an array.
- getColumn(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in column number col as an array.
- getColumn(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in column number col as an array.
- getColumn(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in column number col as an array.
- getColumn(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in column number col as an array.
- getColumnAsDoubleArray(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in column number col as an array
of double values.
- getColumnAsDoubleArray(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in column number col as an array
of double values.
- getColumnDimension() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in interface org.apache.commons.math.linear.AnyMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Returns the number of columns in the matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnVector(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in column number column
as a vector.
- getConditionNumber() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Return the condition number of the matrix.
- getConditionNumber() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Return the condition number of the matrix.
- getConstantTerm() - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Get the constant of the linear equation being optimized.
- getConstraintTypeCounts(Relationship) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get a count of constraints corresponding to a specified relationship.
- getContractionCriteria() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
The contraction criteria defines when the internal array will contract
to store only the number of elements in the element array.
- getConvergence() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the convergence threshold for event localization.
- getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the convergence checker.
- getConvertedMatrix() - Method in class org.apache.commons.math.linear.MatrixUtils.BigFractionMatrixConverter
-
Get the converted matrix.
- getConvertedMatrix() - Method in class org.apache.commons.math.linear.MatrixUtils.FractionMatrixConverter
-
Get the converted matrix.
- getCorrelationMatrix() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Returns the correlation matrix
- getCorrelationMatrix() - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Calculate the Spearman Rank Correlation Matrix.
- getCorrelationPValues() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Returns a matrix of p-values associated with the (two-sided) null
hypothesis that the corresponding correlation coefficient is zero.
- getCorrelationStandardErrors() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Returns a matrix of standard errors associated with the estimates
in the correlation matrix.
getCorrelationStandardErrors().getEntry(i,j) is the standard
error associated with getCorrelationMatrix.getEntry(i,j)
- getCostEvaluations() - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the number of cost evaluations.
- getCount(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- getCount(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values = v.
- getCount(int) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values = v.
- getCount(long) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values = v.
- getCount(char) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values = v.
- getCount(int...) - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Convert to unidimensional counter.
- getCount() - Method in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Get the current unidimensional counter slot.
- getCount(int) - Method in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Get the current count in the selected dimension.
- getCounts(int) - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Convert to multidimensional counter.
- getCounts() - Method in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Get the current multidimensional counter slots.
- getCovariance(double) - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the n × n covariance matrix.
- getCovariance(double) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the n × n covariance matrix.
- getCovariance() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the covariance matrix of the values that have been added.
- getCovariance() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns the covariance of the available values.
- getCovariance() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the covariance matrix of the values that have been added.
- getCovarianceMatrix() - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Returns the covariance matrix
- getCovariances(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the covariance matrix of unbound estimated parameters.
- getCovariances(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
-
Deprecated.
Get the covariance matrix of estimated parameters.
- getCovariances() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the covariance matrix of optimized parameters.
- getCrossoverPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the crossover policy.
- getCrossoverRate() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the crossover rate.
- getCumFreq(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- getCumFreq(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative frequency of values less than or equal to v.
- getCumFreq(int) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative frequency of values less than or equal to v.
- getCumFreq(long) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative frequency of values less than or equal to v.
- getCumFreq(char) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative frequency of values less than or equal to v.
- getCumPct(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- getCumPct(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative percentage of values less than or equal to v
(as a proportion between 0 and 1).
- getCumPct(int) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative percentage of values less than or equal to v
(as a proportion between 0 and 1).
- getCumPct(long) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative percentage of values less than or equal to v
(as a proportion between 0 and 1).
- getCumPct(char) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative percentage of values less than or equal to v
(as a proportion between 0 and 1).
- getCurrentSignedStepsize() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the current signed value of the integration stepsize.
- getCurrentSignedStepsize() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get the current signed value of the integration stepsize.
- getCurrentSignedStepsize() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the current signed value of the integration stepsize.
- getCurrentStepStart() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the current value of the step start time ti.
- getCurrentStepStart() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get the current value of the step start time ti.
- getCurrentStepStart() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Get the current value of the step start time ti.
- getCurrentStepStart() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the current value of the step start time ti.
- getCurrentTime() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the current grid point time.
- getCurrentTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the current grid point time.
- getCurrentTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the current soft grid point time.
- getCurrentTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the current grid point time.
- getD() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the block diagonal matrix D of the decomposition.
- getD() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the block diagonal matrix D of the decomposition.
- getD() - Method in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Gets d parameter value.
- getData() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns vector entries as a double array.
- getData() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns vector entries as a T array.
- getData() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns vector entries as a double array.
- getData() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in interface org.apache.commons.math.linear.FieldVector
-
Returns vector entries as a T array.
- getData() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Returns vector entries as a double array.
- getData() - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getData() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns vector entries as a double array.
- getData() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Returns vector entries as a T array.
- getData() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the tableau data.
- getData() - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Get a copy of the stored data array.
- getDataAsDoubleArray() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getDataAsDoubleArray() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getDataRef() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Get a reference to the stored data array.
- getDecimalDigits() - Method in class org.apache.commons.math.dfp.DfpDec
-
Get the number of decimal digits this class is going to represent.
- getDefaultNumberFormat() - Static method in class org.apache.commons.math.fraction.AbstractFormat
-
Create a default number format.
- getDefaultNumberFormat(Locale) - Static method in class org.apache.commons.math.fraction.AbstractFormat
-
Create a default number format.
- getDefaultNumberFormat() - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Create a default number format.
- getDefaultNumberFormat() - Static method in class org.apache.commons.math.util.CompositeFormat
-
Create a default number format.
- getDefaultNumberFormat(Locale) - Static method in class org.apache.commons.math.util.CompositeFormat
-
Create a default number format.
- getDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
-
Access the degrees of freedom.
- getDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Access the degrees of freedom.
- getDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.TDistribution
-
Access the degrees of freedom.
- getDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Access the degrees of freedom.
- getDelta() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the elevation of the vector.
- getDenominator() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the denominator as a BigInteger.
- getDenominator() - Method in class org.apache.commons.math.fraction.Fraction
-
Access the denominator.
- getDenominatorAsInt() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the denominator as a int.
- getDenominatorAsLong() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the denominator as a long.
- getDenominatorDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.FDistribution
-
Access the denominator degrees of freedom.
- getDenominatorDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the denominator degrees of freedom.
- getDenominatorFormat() - Method in class org.apache.commons.math.fraction.AbstractFormat
-
Access the denominator format.
- getDerivativeException() - Method in exception org.apache.commons.math.ode.events.EventState.EmbeddedDerivativeException
-
Get the embedded exception.
- getDeterminant() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Deprecated.
- getDeterminant() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the determinant of this matrix.
- getDeterminant() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the determinant of this matrix.
- getDeterminant() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
-
Return the determinant of the matrix
- getDeterminant() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Return the determinant of the matrix
- getDeterminant() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Return the determinant of the matrix
- getDeterminant() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Return the determinant of the matrix
- getDeterminant() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Return the determinant of the matrix
- getDeterminant() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Return the determinant of the matrix
- getDeterminant() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Return the determinant of the matrix
- getDeterminant() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Return the determinant of the matrix
- getDeterminant() - Method in interface org.apache.commons.math.linear.RealMatrix
-
- getDeviancePart(double, double) - Static method in class org.apache.commons.math.distribution.SaddlePointExpansion
-
A part of the deviance portion of the saddle point approximation.
- getDimension() - Method in exception org.apache.commons.math.exception.DimensionMismatchException
-
- getDimension() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns the size of the vector.
- getDimension() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the size of the vector.
- getDimension() - Method in interface org.apache.commons.math.linear.FieldVector
-
Returns the size of the vector.
- getDimension() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Returns the size of the vector.
- getDimension() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the size of the vector.
- getDimension() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Returns the size of the vector.
- getDimension() - Method in class org.apache.commons.math.ode.FirstOrderConverter
-
Get the dimension of the problem.
- getDimension() - Method in interface org.apache.commons.math.ode.FirstOrderDifferentialEquations
-
Get the dimension of the problem.
- getDimension() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
-
Deprecated.
Get the dimension of the problem.
- getDimension() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
-
Deprecated.
Get the dimension of the problem.
- getDimension() - Method in class org.apache.commons.math.ode.MultistepIntegrator.CountingDifferentialEquations
-
Get the dimension of the problem.
- getDimension() - Method in interface org.apache.commons.math.ode.SecondOrderDifferentialEquations
-
Get the dimension of the problem.
- getDimension() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the dimension of the data
- getDimension() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns the dimension of the data
- getDimension() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the dimension of the data
- getDimension() - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Get the number of dimensions of the multidimensional counter.
- getDimension1() - Method in exception org.apache.commons.math.DimensionMismatchException
-
Deprecated.
Get the first dimension
- getDimension2() - Method in exception org.apache.commons.math.DimensionMismatchException
-
Deprecated.
Get the second dimension
- getDimensionSizes() - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
-
Get the size in all dimensions.
- getDirection() - Method in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
- getDirection() - Method in enum org.apache.commons.math.stat.descriptive.moment.SemiVariance.Direction
-
Returns the value of this Direction.
- getDistance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getDistance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getDistance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getDistance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getDistance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getDistance(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to compute distance.
- getDistance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getDistance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getDistance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getDistance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getDomain(int, int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Return the domain for the given hypergeometric distribution parameters.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Access the domain value lower bound, based on p, used to
bracket a PDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a PDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a PDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a PDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Access the domain value lower bound, based on p, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Access the domain value upper bound, based on p, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Access the domain value upper bound, based on p, used to
bracket a PDF root.
- getDuplicateAbscissa() - Method in exception org.apache.commons.math.DuplicateSampleAbscissaException
-
Get the duplicate abscissa.
- getE() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant e.
- getEigenvector(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns a copy of the ith eigenvector of the original matrix.
- getEigenvector(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns a copy of the ith eigenvector of the original matrix.
- getElement(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the element at the specified index
- getElement(int) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the element at the specified index
- getElement(int) - Method in interface org.apache.commons.math.util.DoubleArray
-
Returns the element at the specified index.
- getElement(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns the element at the specified index
- getElements() - Method in interface org.apache.commons.math.util.DoubleArray
-
Returns a double[] array containing the elements of this
DoubleArray.
- getElements() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns a double array containing the elements of this
ResizableArray.
- getElitismRate() - Method in class org.apache.commons.math.genetics.ElitisticListPopulation
-
Access the elitism rate.
- getEmpiricalDistribution() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for property empiricalDistribution.
- getEntries() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Get the entries of this instance.
- getEntries() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Get the entries of this instance.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns the entry in the specified index.
- getEntry(int) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int) - Method in interface org.apache.commons.math.linear.FieldVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns the entry in the specified row and column.
- getEntry(int) - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get an entry of the tableau.
- getEntryAsDouble(int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entry in the specified row and column as a double.
- getEntryAsDouble(int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entry in the specified row and column as a double.
- getESplit() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant e split in two pieces.
- getEstimate() - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Get the current estimate of the parameter
- getEvaluations() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the number of evaluations of the differential equations function.
- getEvaluations() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get the number of evaluations of the differential equations function.
- getEvaluations() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the number of evaluations of the differential equations function.
- getEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getEvaluations() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEventException() - Method in exception org.apache.commons.math.ode.events.EventState.EmbeddedEventException
-
Get the embedded exception.
- getEventHandler() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the underlying event handler.
- getEventHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get all the event handlers that have been added to the integrator.
- getEventHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get all the event handlers that have been added to the integrator.
- getEventHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get all the event handlers that have been added to the integrator.
- getEventsHandlers() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Get all the events handlers that have been added to the manager.
- getEventsStates() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Get all the events state wrapping the handlers that have been added to the manager.
- getEventTime() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Get the occurrence time of the first event triggered in the
last evaluated step.
- getEventTime() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the occurrence time of the event triggered in the current step.
- getExpansionFactor() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
The expansion factor controls the size of a new array when an array
needs to be expanded.
- getExpansionMode() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
The expansionMode determines whether the internal storage
array grows additively (ADDITIVE_MODE) or multiplicatively
(MULTIPLICATIVE_MODE) when it is expanded.
- getExponent() - Method in interface org.apache.commons.math.distribution.ZipfDistribution
-
Get the exponent characterising the distribution.
- getExponent() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Get the exponent characterising the distribution.
- getExponent(double) - Static method in class org.apache.commons.math.util.FastMath
-
Return the exponent of a double number, removing the bias.
- getExponent(float) - Static method in class org.apache.commons.math.util.FastMath
-
Return the exponent of a float number, removing the bias.
- getFarthestPoint(Collection<Cluster<T>>) - Method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Get the point farthest to its cluster center
- getFHi() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getField() - Method in class org.apache.commons.math.complex.Complex
-
Get the
Field to which the instance belongs.
- getField() - Method in class org.apache.commons.math.dfp.Dfp
-
- getField() - Method in interface org.apache.commons.math.FieldElement
-
Get the
Field to which the instance belongs.
- getField() - Method in class org.apache.commons.math.fraction.BigFraction
-
Get the
Field to which the instance belongs.
- getField() - Method in class org.apache.commons.math.fraction.Fraction
-
Get the
Field to which the instance belongs.
- getField() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Get the type of field elements of the matrix.
- getField() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Get the type of field elements of the vector.
- getField() - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Get the type of field elements of the matrix.
- getField() - Method in interface org.apache.commons.math.linear.FieldVector
-
Get the type of field elements of the vector.
- getField() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Get the type of field elements of the vector.
- getField() - Method in class org.apache.commons.math.util.BigReal
-
Get the
Field to which the instance belongs.
- getFinalTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Get the final integration time.
- getFirst() - Method in class org.apache.commons.math.genetics.ChromosomePair
-
Access the first chromosome.
- getFitness() - Method in class org.apache.commons.math.genetics.Chromosome
-
Access the fitness of this chromosome.
- getFittestChromosome() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Access the fittest chromosome in this population.
- getFittestChromosome() - Method in interface org.apache.commons.math.genetics.Population
-
Access the fittest chromosome in this population.
- getFLow() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getFMid() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getFormat() - Method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the components format.
- getFormat() - Method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the components format.
- getFrobeniusNorm() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
- getFrobeniusNorm() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
- getFrobeniusNorm() - Method in interface org.apache.commons.math.linear.RealMatrix
-
- getFunctionValue() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Get the result of the last run of the solver.
- getFunctionValue() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Get the result of the last run of the solver.
- getFunctionValue() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getFunctionValue() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getFunctionValue() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getFunctionValueAccuracy() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Get the actual function value accuracy.
- getFunctionValueAccuracy() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Get the actual function value accuracy.
- getGeneralPattern() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in exception org.apache.commons.math.MathException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGenerationsEvolved() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the number of generations evolved to
reach
StoppingCondition in the last run.
- getGenerator() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Get the underlying normalized components generator.
- getGeneratorUpperBounds() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Returns a fresh copy of the array of upper bounds of the subintervals
of [0,1] used in generating data from the empirical distribution.
- getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured geometric mean implementation
- getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured geometric mean implementation
- getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured geometric mean implementation
- getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured geometric mean implementation
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the geometric mean of all the aggregated data.
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getGeometricMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
geometric mean of the ith entries of the arrays
that correspond to each multivariate sample
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the geometric mean of the values that have been added.
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the geometric mean of the values that have been added.
- getGeometricMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured geometric mean implementation.
- getGlobalCurrentTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the current global grid point time.
- getGlobalPreviousTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the previous global grid point time.
- getGoalType() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- getGradientEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the number of evaluations of the objective function gradient.
- getGradientEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the number of evaluations of the objective function gradient.
- getGradientEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the number of evaluations of the objective function gradient.
- getGuessedAmplitude() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Get the guessed amplitude a.
- getGuessedPhase() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Get the guessed phase φ.
- getGuessedPulsation() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Get the guessed pulsation ω.
- getH() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Returns the Householder reflector vectors.
- getH() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Returns the Householder reflector vectors.
- getHandler() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.EventHandlerWrapper
-
Deprecated.
Get the underlying event handler with jacobians.
- getHandler() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
-
Deprecated.
Get the underlying step handler with jacobians.
- getHeight() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the height of the tableau.
- getHi() - Method in exception org.apache.commons.math.exception.OutOfRangeException
-
- getHi() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getHouseholderVectorsRef() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Get the Householder vectors of the transform.
- getHouseholderVectorsRef() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Get the Householder vectors of the transform.
- getIEEEFlags() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the IEEE 854 status flags.
- getImagEigenvalue(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the imaginary part of the ith eigenvalue of the original matrix.
- getImagEigenvalue(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the imaginary part of the ith eigenvalue of the original matrix.
- getImagEigenvalues() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns a copy of the imaginary parts of the eigenvalues of the original matrix.
- getImagEigenvalues() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns a copy of the imaginary parts of the eigenvalues of the original matrix.
- getImaginary() - Method in class org.apache.commons.math.complex.Complex
-
Access the imaginary part.
- getImaginaryCharacter() - Method in class org.apache.commons.math.complex.ComplexFormat
-
Access the imaginaryCharacter.
- getImaginaryFormat() - Method in class org.apache.commons.math.complex.ComplexFormat
-
Access the imaginaryFormat.
- getImproperInstance() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Returns the default complex format for the current locale.
- getImproperInstance(Locale) - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Returns the default complex format for the given locale.
- getImproperInstance() - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Returns the default complex format for the current locale.
- getImproperInstance(Locale) - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Returns the default complex format for the given locale.
- getIndex() - Method in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
Get the index of the wrong value.
- getIndex() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
-
Get the index of the entry.
- getIndex() - Method in class org.apache.commons.math.linear.RealVector.Entry
-
Get the index of the entry.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the initial domain value, based on p, used to
bracket a CDF root.
- getInitialTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Get the initial integration time.
- getInstance() - Static method in class org.apache.commons.math.complex.ComplexField
-
Get the unique instance.
- getInstance() - Static method in class org.apache.commons.math.complex.ComplexFormat
-
Returns the default complex format for the current locale.
- getInstance(Locale) - Static method in class org.apache.commons.math.complex.ComplexFormat
-
Returns the default complex format for the given locale.
- getInstance() - Static method in class org.apache.commons.math.fraction.BigFractionField
-
Get the unique instance.
- getInstance() - Static method in class org.apache.commons.math.fraction.FractionField
-
Get the unique instance.
- getInstance() - Static method in class org.apache.commons.math.geometry.Vector3DFormat
-
Returns the default 3D vector format for the current locale.
- getInstance(Locale) - Static method in class org.apache.commons.math.geometry.Vector3DFormat
-
Returns the default 3D vector format for the given locale.
- getInstance() - Static method in class org.apache.commons.math.linear.RealVectorFormat
-
Returns the default real vector format for the current locale.
- getInstance(Locale) - Static method in class org.apache.commons.math.linear.RealVectorFormat
-
Returns the default real vector format for the given locale.
- getInstance(int) - Static method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Get the Nordsieck transformer for a given number of steps.
- getInstance() - Static method in class org.apache.commons.math.ode.sampling.DummyStepHandler
-
Get the only instance.
- getInstance() - Static method in class org.apache.commons.math.util.BigRealField
-
Get the unique instance.
- getIntercept() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the intercept of the estimated regression line.
- getIntercept(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the intercept of the estimated regression line, given the slope.
- getInterceptStdErr() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getInternalLength() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Notice the package scope on this method.
- getInternalValues() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns the internal storage array.
- getInterpolatedDerivatives() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the derivatives of the state vector of the interpolated point.
- getInterpolatedDerivatives() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the derivatives of the state vector of the interpolated point.
- getInterpolatedDyDp() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the partial derivatives of the state vector with respect to
the ODE parameters of the interpolated point.
- getInterpolatedDyDp() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the partial derivatives of the state vector with respect to
the ODE parameters of the interpolated point.
- getInterpolatedDyDpDot() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the time derivatives of the jacobian of the state vector
with respect to the ODE parameters of the interpolated point.
- getInterpolatedDyDpDot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the time derivatives of the jacobian of the state vector
with respect to the ODE parameters of the interpolated point.
- getInterpolatedDyDy0() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the partial derivatives of the state vector with respect to
the initial state of the interpolated point.
- getInterpolatedDyDy0() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the partial derivatives of the state vector with respect to
the initial state of the interpolated point.
- getInterpolatedDyDy0Dot() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the time derivatives of the jacobian of the state vector
with respect to the initial state of the interpolated point.
- getInterpolatedDyDy0Dot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the time derivatives of the jacobian of the state vector
with respect to the initial state of the interpolated point.
- getInterpolatedState() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Get the state vector of the interpolated point.
- getInterpolatedState() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the state vector of the interpolated point.
- getInterpolatedState() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the state vector of the interpolated point.
- getInterpolatedStateVariation() - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Get the state vector variation from current to interpolated state.
- getInterpolatedTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Get the time of the interpolated point.
- getInterpolatedTime() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the time of the interpolated point.
- getInterpolatedTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the time of the interpolated point.
- getInterpolatedTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the time of the interpolated point.
- getInterpolatedTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the time of the interpolated point.
- getInterpolatedY() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the state vector of the interpolated point.
- getInterpolatedY() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the state vector of the interpolated point.
- getInterpolatedYDot() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the time derivatives of the state vector of the interpolated point.
- getInterpolatedYDot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the time derivatives of the state vector of the interpolated point.
- getInterpolatingPoints() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Returns a copy of the interpolating points array.
- getInterpolatingValues() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Returns a copy of the interpolating values array.
- getInterpolationPointsForY(WeightedObservedPoint[], int, int, double) - Method in class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
-
Gets the two bounding interpolation points from the specified points
suitable for determining X at the specified Y.
- getInverse() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
-
Get the inverse (or pseudo-inverse) of the decomposed matrix.
- getInverse() - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Get the inverse (or pseudo-inverse) of the decomposed matrix.
- getInverse() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
-
Get the inverse of the decomposed matrix.
- getInverse() - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Get the inverse (or pseudo-inverse) of the decomposed matrix.
- getInverse() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
-
Get the inverse (or pseudo-inverse) of the decomposed matrix.
- getInverse() - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
-
Get the inverse (or pseudo-inverse) of the decomposed matrix.
- getInverse() - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
-
Get the inverse (or pseudo-inverse) of the decomposed matrix.
- getInverse() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
-
Get the pseudo-inverse of the decomposed matrix.
- getInvertedCoeffiecientSum(RealVector) - Static method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the -1 times the sum of all coefficients in the given array.
- getIterationCount() - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Get the number of iterations in the last run of the algorithm.
- getIterationCount() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Get the number of iterations in the last run of the algorithm.
- getIterationCount() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the number of iterations in the last run of the algorithm.
- getIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getJacobianEvaluations() - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the number of jacobian evaluations.
- getJacobianEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the number of evaluations of the objective function jacobian .
- getJacobianEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the number of evaluations of the objective function jacobian .
- getJacobianEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the number of evaluations of the objective function jacobian .
- getKnots() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
-
Returns an array copy of the knot points.
- getKurtosis() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the Kurtosis of the available values.
- getKurtosisImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured kurtosis implementation.
- getL() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
-
Returns the matrix L of the decomposition.
- getL() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Returns the matrix L of the decomposition.
- getL() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Returns the matrix L of the decomposition.
- getL() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Returns the matrix L of the decomposition.
- getL() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Returns the matrix L of the decomposition.
- getL() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Returns the matrix L of the decomposition.
- getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getL1Distance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getL1Distance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getL1Distance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getL1Distance(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getL1Distance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getL1Distance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getL1Distance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getL1Norm() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns the L1 norm of the vector.
- getL1Norm() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the L1 norm of the vector.
- getL1Norm() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the L1 norm of the vector.
- getLength() - Method in class org.apache.commons.math.genetics.AbstractListChromosome
-
Returns the length of the chromosome.
- getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getLInfDistance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getLInfDistance(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to compute LInfDistance.
- getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getLInfDistance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getLInfDistance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getLInfNorm() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns the L∞ norm of the vector.
- getLInfNorm() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the L∞ norm of the vector.
- getLInfNorm() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the L∞ norm of the vector.
- getLn10() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(10).
- getLn2() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(2).
- getLn2Split() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(2) split in two pieces.
- getLn5() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(5).
- getLn5Split() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(5) split in two pieces.
- getLo() - Method in exception org.apache.commons.math.exception.OutOfRangeException
-
- getLo() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getLocalizedMessage() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in exception org.apache.commons.math.MathException
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the message in the system default locale.
- getLocalizedString(Locale) - Method in class org.apache.commons.math.exception.util.DummyLocalizable
-
Get the localized string.
- getLocalizedString(Locale) - Method in interface org.apache.commons.math.exception.util.Localizable
-
Get the localized string.
- getLocalizedString(Locale) - Method in enum org.apache.commons.math.exception.util.LocalizedFormats
-
Get the localized string.
- getLowerDomain(int, int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Return the lowest domain value for the given hypergeometric distribution
parameters.
- getLT() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
-
Returns the transpose of the matrix L of the decomposition.
- getLT() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Returns the transpose of the matrix L of the decomposition.
- getLUMatrix() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the LU decomposition as a BigMatrix.
- getMainDiagonalRef() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Get the main diagonal elements of the matrix B of the transform.
- getMainDiagonalRef() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Get the main diagonal elements of the matrix T of the transform.
- getMainSetDimension() - Method in interface org.apache.commons.math.ode.ExtendedFirstOrderDifferentialEquations
-
Return the dimension of the main set of equations.
- getMainSetDimension() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.MappingWrapper
-
Deprecated.
Return the dimension of the main set of equations.
- getMainSetDimension() - Method in class org.apache.commons.math.ode.MultistepIntegrator.CountingDifferentialEquations
-
Return the dimension of the main set of equations.
- getMatrix() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the 3X3 matrix corresponding to the instance
- getMax() - Method in exception org.apache.commons.math.exception.NumberIsTooLargeException
-
- getMax() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- getMax() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the maximum of the available values
- getMax() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the maximum of the available values
- getMax() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getMax() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
maximum of the ith entries of the arrays
that correspond to each multivariate sample
- getMax() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the maximum of the available values
- getMax() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getMax() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the maximum of the values that have been added.
- getMax() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getMax() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the maximum of the values that have been added.
- getMaxCheckInterval() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the maximal time interval between events handler checks.
- getMaxEvaluations() - Method in exception org.apache.commons.math.MaxEvaluationsExceededException
-
Get the maximal number of evaluations allowed.
- getMaxEvaluations() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxGrowth() - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Get the maximal growth factor for stepsize control.
- getMaxGrowth() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Get the maximal growth factor for stepsize control.
- getMaximalIterationCount() - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Get the upper limit for the number of iterations.
- getMaximalIterationCount() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Get the upper limit for the number of iterations.
- getMaximalIterationCount() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the upper limit for the number of iterations.
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured maximum implementation.
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured maximum implementation
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured maximum implementation
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured maximum implementation
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured maximum implementation
- getMaxIndex() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Get the index of the maximum entry.
- getMaxIterationCount() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the upper limit in the iteration count for event localization.
- getMaxIterations() - Method in exception org.apache.commons.math.MaxIterationsExceededException
-
Get the maximal number of iterations allowed.
- getMaxIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxStep() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Get the maximal step.
- getMaxValue() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Get the value of the maximum entry.
- getMean() - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
-
Access the mean.
- getMean() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Access the mean.
- getMean() - Method in interface org.apache.commons.math.distribution.NormalDistribution
-
Access the mean.
- getMean() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the mean.
- getMean() - Method in interface org.apache.commons.math.distribution.PoissonDistribution
-
Get the mean for the distribution.
- getMean() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Get the Poisson mean for the distribution.
- getMean() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
mean of the ith entries of the arrays
that correspond to each multivariate sample
- getMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the mean of the values that have been added.
- getMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the mean of the values that have been added.
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured mean implementation.
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured mean implementation
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured mean implementation
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured mean implementation
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured mean implementation
- getMeanSquareError() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of squared errors divided by the degrees of freedom,
usually abbreviated MSE.
- getMeasuredValue() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Get the measured value
- getMeasurements() - Method in interface org.apache.commons.math.estimation.EstimationProblem
-
Deprecated.
Get the measurements of an estimation problem.
- getMeasurements() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Get the measurements of an estimation problem.
- getMedian() - Method in interface org.apache.commons.math.distribution.CauchyDistribution
-
Access the median.
- getMedian() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the median.
- getMessage(Locale) - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Get the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Get the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the message in a specified locale.
- getMessage() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Get the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in exception org.apache.commons.math.MathException
-
Gets the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.MathException
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the message in a conventional US locale.
- getMid() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getMin() - Method in exception org.apache.commons.math.exception.NumberIsTooSmallException
-
- getMin() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- getMin() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the minimum of the available values
- getMin() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the minimum of the available values
- getMin() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getMin() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
minimum of the ith entries of the arrays
that correspond to each multivariate sample
- getMin() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the minimum of the available values
- getMin() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getMin() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the minimum of the values that have been added.
- getMin() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getMin() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the minimum of the values that have been added.
- getMinimalIterationCount() - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
-
Get the lower limit for the number of iterations.
- getMinimalIterationCount() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Get the lower limit for the number of iterations.
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured minimum implementation.
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured minimum implementation
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured minimum implementation
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured minimum implementation
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured minimum implementation
- getMinIndex() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Get the index of the minimum entry.
- getMinReduction() - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Get the minimal reduction factor for stepsize control.
- getMinReduction() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Get the minimal reduction factor for stepsize control.
- getMinStep() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Get the minimal step.
- getMinValue() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Get the value of the minimum entry.
- getMode() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for property mode.
- getMu() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for property mu.
- getMutationPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the mutation policy.
- getMutationRate() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the mutation rate.
- getN() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
-
Returns the number of spline segments = the number of polynomials
= the number of knot points - 1.
- getN() - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Returns the number of observations (length of covariate vectors)
- getN() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Get the number of vectors in the sample.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
-
Get the number of vectors in the sample.
- getN() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Returns the number of values that have been added.
- getN() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns the number of available values
- getN() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getN() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the number of observations that have been added to the model.
- getName() - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
get the name of the parameter
- getName() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the name of the method.
- getName() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the name of the method.
- getNanPositions(NaturalRanking.IntDoublePair[]) - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
-
Returns a list of indexes where ranks is NaN.
- getNanStrategy() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
-
Return the NaNStrategy
- getNatural(int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Returns an array representing n.
- getNearestCluster(Collection<Cluster<T>>, T) - Static method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Returns the nearest
Cluster to the given point
- getNewtonCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Returns a copy of coefficients in Newton form formula.
- getNext() - Method in class org.apache.commons.math.random.ValueServer
-
Returns the next generated value, generated according
to the mode value (see MODE constants).
- getNextDigest() - Method in class org.apache.commons.math.random.ValueServer
-
Gets a random value in DIGEST_MODE.
- getNextExponential() - Method in class org.apache.commons.math.random.ValueServer
-
Gets an exponentially distributed random value with mean = mu.
- getNextGaussian() - Method in class org.apache.commons.math.random.ValueServer
-
Gets a Gaussian distributed random value with mean = mu
and standard deviation = sigma.
- getNextReplay() - Method in class org.apache.commons.math.random.ValueServer
-
Gets next sequential value from the valuesFileURL.
- getNextUniform() - Method in class org.apache.commons.math.random.ValueServer
-
Gets a uniformly distributed random value with mean = mu.
- getNextValue() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Generates a random value from this distribution.
- getNextValue() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Generates a random value from this distribution.
- getNorm() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the L2 norm for the vector.
- getNorm() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
- getNorm() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns the L2 norm of the vector.
- getNorm() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the L2 norm of the vector.
- getNorm() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
- getNorm() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
- getNorm() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
- getNorm() - Method in interface org.apache.commons.math.linear.RealMatrix
-
- getNorm() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the L2 norm of the vector.
- getNorm() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the L2 norm of the matrix.
- getNorm() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the L2 norm of the matrix.
- getNorm1() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the L1 norm for the vector.
- getNormInf() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the L∞ norm for the vector.
- getNormSq() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the square of the norm for the vector.
- getNSteps() - Method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Get the number of steps of the method
(excluding the one being computed).
- getNumArtificialVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the number of artificial variables.
- getNumberOfElements() - Method in interface org.apache.commons.math.distribution.ZipfDistribution
-
Get the number of elements (e.g.
- getNumberOfElements() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Get the number of elements (e.g.
- getNumberOfSuccesses() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
Access the number of successes.
- getNumberOfSuccesses() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the number of successes.
- getNumberOfSuccesses() - Method in interface org.apache.commons.math.distribution.PascalDistribution
-
Access the number of successes for this distribution.
- getNumberOfSuccesses() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Access the number of successes for this distribution.
- getNumberOfTrials() - Method in interface org.apache.commons.math.distribution.BinomialDistribution
-
Access the number of trials for this distribution.
- getNumberOfTrials() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Access the number of trials for this distribution.
- getNumDecisionVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the number of decision variables.
- getNumElements() - Method in interface org.apache.commons.math.util.DoubleArray
-
Returns the number of elements currently in the array.
- getNumElements() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns the number of elements currently in the array.
- getNumerator() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the numerator as a BigInteger.
- getNumerator() - Method in class org.apache.commons.math.fraction.Fraction
-
Access the numerator.
- getNumeratorAsInt() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the numerator as a int.
- getNumeratorAsLong() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the numerator as a long.
- getNumeratorDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.FDistribution
-
Access the numerator degrees of freedom.
- getNumeratorDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the numerator degrees of freedom.
- getNumeratorFormat() - Method in class org.apache.commons.math.fraction.AbstractFormat
-
Access the numerator format.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Returns the mean of the distribution.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Returns the mean of the distribution.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Returns the mean of the distribution.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Returns the mean of the distribution.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Returns the mean.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Returns the variance.
- getNumGenerations() - Method in class org.apache.commons.math.genetics.FixedGenerationCount
-
- getNumObjectiveFunctions() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the number of objective functions in this tableau.
- getNumSlackVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the number of slack variables.
- getObservations() - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Get the observed points.
- getOmegaImaginary(int) - Method in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
-
Get the imaginary part of the kth nth root of unity
- getOmegaInverse() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Get the inverse of the covariance.
- getOmegaReal(int) - Method in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
-
Get the real part of the kth nth root of unity
- getOne() - Method in class org.apache.commons.math.complex.ComplexField
-
Get the multiplicative identity of the field.
- getOne() - Method in class org.apache.commons.math.dfp.Dfp
-
Get the constant 1.
- getOne() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant 1.
- getOne() - Method in interface org.apache.commons.math.Field
-
Get the multiplicative identity of the field.
- getOne() - Method in class org.apache.commons.math.fraction.BigFractionField
-
Get the multiplicative identity of the field.
- getOne() - Method in class org.apache.commons.math.fraction.FractionField
-
Get the multiplicative identity of the field.
- getOne() - Method in class org.apache.commons.math.util.BigRealField
-
Get the multiplicative identity of the field.
- getOneWayAnova() - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0
- getOptima() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get all the optima found during the last call to
optimize.
- getOptima() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get all the optima found during the last call to
optimize.
- getOptima() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get all the optima found during the last call to
optimize.
- getOptima() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get all the optima found during the last call to
optimize.
- getOptimaValues() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get all the function values at optima found during the last call to
optimize.
- getOptimum() - Method in class org.apache.commons.math.optimization.direct.PowellOptimizer.LineSearch
-
- getOrder() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Get the order of the method.
- getOrder() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Get the order of the method.
- getOrder() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Get the order of the method.
- getOrder() - Method in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
-
Get the order of the method.
- getOriginalNumDecisionVariables() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the original number of decision variables.
- getP() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Returns the P rows permutation matrix.
- getP() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Returns the P rows permutation matrix.
- getP() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Returns the P rows permutation matrix.
- getP() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Returns the P rows permutation matrix.
- getParametersDimension() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.FiniteDifferencesWrapper
-
Deprecated.
Get the number of parameters.
- getParametersDimension() - Method in interface org.apache.commons.math.ode.jacobians.ODEWithJacobians
-
Deprecated.
Get the number of parameters.
- getParametersDimension() - Method in interface org.apache.commons.math.ode.jacobians.ParameterizedODE
-
Deprecated.
Get the number of parameters.
- getPartial(EstimatedParameter) - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
- getPattern() - Method in exception org.apache.commons.math.MathException
-
- getPattern() - Method in exception org.apache.commons.math.MathRuntimeException
-
- getPct(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- getPct(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the percentage of values that are equal to v
(as a proportion between 0 and 1).
- getPct(int) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the percentage of values that are equal to v
(as a proportion between 0 and 1).
- getPct(long) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the percentage of values that are equal to v
(as a proportion between 0 and 1).
- getPct(char) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the percentage of values that are equal to v
(as a proportion between 0 and 1).
- getPercentile(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns an estimate for the pth percentile of the stored values.
- getPercentileImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured percentile implementation.
- getPermutation() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the permutation associated with the lu decomposition.
- getPhase() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
-
Get the phase φ.
- getPi() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant π.
- getPiSplit() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant π split in two pieces.
- getPivot() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Returns the pivot permutation vector.
- getPivot() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Returns the pivot permutation vector.
- getPivot() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Returns the pivot permutation vector.
- getPivot() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Returns the pivot permutation vector.
- getPivotColumn(SimplexTableau) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
-
Returns the column with the most negative coefficient in the objective function row.
- getPivotRow(SimplexTableau, int) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
-
Returns the row with the minimum ratio as given by the minimum ratio test (MRT).
- getPoint() - Method in class org.apache.commons.math.optimization.RealPointValuePair
-
Get the point.
- getPoint() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Get the point.
- getPoint() - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
-
Get the n-dimensional point in integer space.
- getPointFromLargestNumberCluster(Collection<Cluster<T>>) - Method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Get a random point from the
Cluster with the largest number of points
- getPointFromLargestVarianceCluster(Collection<Cluster<T>>) - Method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Get a random point from the
Cluster with the largest distance variance.
- getPointRef() - Method in class org.apache.commons.math.optimization.RealPointValuePair
-
Get a reference to the point.
- getPointRef() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Get a reference to the point.
- getPoints() - Method in class org.apache.commons.math.stat.clustering.Cluster
-
Get the points contained in the cluster.
- getPolynomialFunction() - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
as of 2.0 the function is not stored anymore within the instance.
- getPolynomials() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
-
Returns a copy of the interpolating polynomials array.
- getPopulationLimit() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Access the maximum population size.
- getPopulationLimit() - Method in interface org.apache.commons.math.genetics.Population
-
Access the maximum population size.
- getPopulationSize() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
Access the population size.
- getPopulationSize() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the population size.
- getPopulationSize() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Access the current population size.
- getPopulationSize() - Method in interface org.apache.commons.math.genetics.Population
-
Access the current population size.
- getPosition() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
-
Returns the original position of the pair.
- getPrefix() - Method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the format prefix.
- getPrefix() - Method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the format prefix.
- getPrevious() - Method in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
- getPreviousTime() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Get the previous grid point time.
- getPreviousTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the previous grid point time.
- getPreviousTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the previous soft grid point time.
- getPreviousTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the previous grid point time.
- getProbabilityOfSuccess() - Method in interface org.apache.commons.math.distribution.BinomialDistribution
-
Access the probability of success for this distribution.
- getProbabilityOfSuccess() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Access the probability of success for this distribution.
- getProbabilityOfSuccess() - Method in interface org.apache.commons.math.distribution.PascalDistribution
-
Access the probability of success for this distribution.
- getProbabilityOfSuccess() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Access the probability of success for this distribution.
- getProperInstance() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Returns the default complex format for the current locale.
- getProperInstance(Locale) - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Returns the default complex format for the given locale.
- getProperInstance() - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Returns the default complex format for the current locale.
- getProperInstance(Locale) - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Returns the default complex format for the given locale.
- getPulsation() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
-
Get the pulsation ω.
- getQ() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Returns the matrix Q of the decomposition.
- getQ() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Returns the matrix Q of the decomposition.
- getQ() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Returns the matrix Q of the transform.
- getQ0() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the scalar coordinate of the quaternion.
- getQ1() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the first coordinate of the vectorial part of the quaternion.
- getQ2() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the second coordinate of the vectorial part of the quaternion.
- getQ3() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the third coordinate of the vectorial part of the quaternion.
- getQT() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Returns the transpose of the matrix Q of the decomposition.
- getQT() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Returns the transpose of the matrix Q of the decomposition.
- getQT() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Returns the transpose of the matrix Q of the transform.
- getQuantile() - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Returns the value of the quantile field (determines what percentile is
computed when evaluate() is called with no quantile argument).
- getR() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Returns the matrix R of the decomposition.
- getR() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Returns the matrix R of the decomposition.
- getR() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getRadixDigits() - Method in class org.apache.commons.math.dfp.Dfp
-
Get the number of radix digits of the instance.
- getRadixDigits() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the number of radix digits of the
Dfp instances built by this factory.
- getRan() - Method in class org.apache.commons.math.random.RandomDataImpl
-
Returns the RandomGenerator used to generate non-secure random data.
- getRandomGenerator() - Static method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the (static) random generator.
- getRank() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Return the effective numerical matrix rank.
- getRank() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Return the effective numerical matrix rank.
- getRank() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Get the rank of the covariance matrix.
- getRankCorrelation() - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
- getReal() - Method in class org.apache.commons.math.complex.Complex
-
Access the real part.
- getRealEigenvalue(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the real part of the ith eigenvalue of the original matrix.
- getRealEigenvalue(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the real part of the ith eigenvalue of the original matrix.
- getRealEigenvalues() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns a copy of the real parts of the eigenvalues of the original matrix.
- getRealEigenvalues() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns a copy of the real parts of the eigenvalues of the original matrix.
- getRealFormat() - Method in class org.apache.commons.math.complex.ComplexFormat
-
Access the realFormat.
- getReducedFraction(int, int) - Static method in class org.apache.commons.math.fraction.BigFraction
-
Creates a BigFraction instance with the 2 parts of a fraction
Y/Z.
- getReducedFraction(int, int) - Static method in class org.apache.commons.math.fraction.Fraction
-
Creates a Fraction instance with the 2 parts
of a fraction Y/Z.
- getRegressionSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of squared deviations of the predicted y values about
their mean (which equals the mean of y).
- getRegressionSumSquares(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Computes SSR from b1.
- getRelationship() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
-
Get the relationship between left and right hand sides.
- getRelativeAccuracy() - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Get the actual relative accuracy.
- getRelativeAccuracy() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Get the actual relative accuracy.
- getRelativeAccuracy() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the actual relative accuracy.
- getRepresentation() - Method in class org.apache.commons.math.genetics.AbstractListChromosome
-
Returns the (immutable) inner representation of the chromosome.
- getResidual() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Get the residual for this measurement
The residual is the measured value minus the theoretical value.
- getResult() - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
-
Get the result of the last run of the integrator.
- getResult() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Access the last computed integral.
- getResult() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Get the result of the last run of the solver.
- getResult() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Get the result of the last run of the solver.
- getResult() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getResult() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getResult() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Returns the value of the statistic based on the values that have been added.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Get the covariance matrix.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
-
Get the mean vector.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Returns the current value of the Statistic.
- getResult() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Returns the current value of the Statistic.
- getResults(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns an array of the results of a statistic.
- getRhsOffset() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the offset of the right hand side.
- getRMS(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the Root Mean Square value.
- getRMS(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
-
Deprecated.
Get the Root Mean Square value.
- getRMS() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the Root Mean Square value.
- getRootMatrix() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Get the root of the covariance matrix.
- getRoundingMode() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the current rounding mode.
- getRoundingMode() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Gets the rounding mode
- getRoundingMode() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Gets the rounding mode for division operations
The default is BigDecimal.ROUND_HALF_UP
- getRoundingMode() - Method in class org.apache.commons.math.util.BigReal
-
Gets the rounding mode for division operations
The default is RoundingMode.HALF_UP
- getRow(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in row number row as an array.
- getRow(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in row number row as an array.
- getRow(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in row number row as an array.
- getRow(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in row number row as an array.
- getRow(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in row number row as an array.
- getRow(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in row number row as an array.
- getRow(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in row number row as an array.
- getRow(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in row number row as an array.
- getRowAsDoubleArray(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in row number row as an array
of double values.
- getRowAsDoubleArray(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in row number row as an array
of double values.
- getRowDimension() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in interface org.apache.commons.math.linear.AnyMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Returns the number of rows in the matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowVector(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in row number row
as a vector.
- getRSquare() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getS() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the diagonal matrix Σ of the decomposition.
- getS() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the diagonal matrix Σ of the decomposition.
- getSafety() - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Get the safety factor for stepsize control.
- getSafety() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Get the safety factor for stepsize control.
- getSampleSize() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
Access the sample size.
- getSampleSize() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the sample size.
- getSampleStats() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
- getSampleStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
- getScale() - Method in interface org.apache.commons.math.distribution.CauchyDistribution
-
Access the scale parameter.
- getScale() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the scale parameter.
- getScale() - Method in interface org.apache.commons.math.distribution.WeibullDistribution
-
Access the scale parameter.
- getScale() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the scale parameter.
- getScale() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Sets the scale for division operations.
- getScale() - Method in class org.apache.commons.math.util.BigReal
-
Sets the scale for division operations.
- getSecond() - Method in class org.apache.commons.math.genetics.ChromosomePair
-
Access the second chromosome.
- getSecondaryDiagonalRef() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Get the secondary diagonal elements of the matrix B of the transform.
- getSecondaryDiagonalRef() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Get the secondary diagonal elements of the matrix T of the transform.
- getSecondMoment() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns a statistic related to the Second Central Moment.
- getSecondMoment() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns a statistic related to the Second Central Moment.
- getSecRan() - Method in class org.apache.commons.math.random.RandomDataImpl
-
Returns the SecureRandom used to generate secure random data.
- getSelectionPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the selection policy.
- getSeparator() - Method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the format separator between components.
- getSeparator() - Method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the format separator between components.
- getShape() - Method in interface org.apache.commons.math.distribution.WeibullDistribution
-
Access the shape parameter.
- getShape() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the shape parameter.
- getSigma() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for property sigma.
- getSignificance() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the significance level of the slope (equiv) correlation.
- getSingularValues() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the diagonal elements of the matrix Σ of the decomposition.
- getSingularValues() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the diagonal elements of the matrix Σ of the decomposition.
- getSize() - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Get the total number of elements.
- getSizes() - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Get the number of multidimensional counter slots in each dimension.
- getSkewness() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the skewness of the available values.
- getSkewnessImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured skewness implementation.
- getSlackVariableOffset() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the offset of the first slack variable.
- getSlope() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the slope of the estimated regression line.
- getSlopeConfidenceInterval() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the half-width of a 95% confidence interval for the slope
estimate.
- getSlopeConfidenceInterval(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the half-width of a (100-100*alpha)% confidence interval for
the slope estimate.
- getSlopeStdErr() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getSolution() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the current solution.
- getSolver() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Returns the solver absolute accuracy for inverse cumulative computation.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSortedValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the current set of values in an array of double primitives,
sorted in ascending order.
- getSourceString() - Method in class org.apache.commons.math.exception.util.DummyLocalizable
-
Get the source (non-localized) string.
- getSourceString() - Method in interface org.apache.commons.math.exception.util.Localizable
-
Get the source (non-localized) string.
- getSourceString() - Method in enum org.apache.commons.math.exception.util.LocalizedFormats
-
Get the source (non-localized) string.
- getSparcity() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
- getSparsity() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
- getSpecificPattern() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in exception org.apache.commons.math.MathException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSqr2() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √2.
- getSqr2Reciprocal() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √2 / 2.
- getSqr2Split() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √2 split in two pieces.
- getSqr3() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √3.
- getSqr3Reciprocal() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √3 / 3.
- getStandardDeviation() - Method in interface org.apache.commons.math.distribution.NormalDistribution
-
Access the standard deviation.
- getStandardDeviation() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the standard deviation.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the standard deviation of the available values.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the standard deviation of the available values.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getStandardDeviation() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
standard deviation of the ith entries of the arrays
that correspond to each multivariate sample
- getStandardDeviation() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the standard deviation of the available values.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the standard deviation of the values that have been added.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the standard deviation of the available values.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the standard deviation of the values that have been added.
- getStarterIntegrator() - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Get the starter integrator.
- getStartValue() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- getStepHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get all the step handlers that have been added to the integrator.
- getStepHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get all the step handlers that have been added to the integrator.
- getStepHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get all the step handlers that have been added to the integrator.
- getStirlingError(double) - Static method in class org.apache.commons.math.distribution.SaddlePointExpansion
-
Compute the error of Stirling's series at the given value.
- getStrict() - Method in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Gets a submatrix.
- getSubVector(int, int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in interface org.apache.commons.math.linear.FieldVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in interface org.apache.commons.math.linear.RealVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Get a subvector from consecutive elements.
- getSuffix() - Method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the format suffix.
- getSuffix() - Method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the format suffix.
- getSum() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the sum of the values that have been added to Univariate.
- getSum() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the sum of the values that have been added to Univariate.
- getSum() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getSum() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
sum of the ith entries of the arrays
that correspond to each multivariate sample
- getSum() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the sum of the values that have been added to Univariate.
- getSum() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getSum() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the sum of the values that have been added
- getSum() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getSum() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the sum of the values that have been added
- getSumFreq() - Method in class org.apache.commons.math.stat.Frequency
-
Returns the sum of all frequencies.
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured sum implementation.
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured Sum implementation
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured Sum implementation
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured Sum implementation
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured Sum implementation
- getSumLog() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getSumLog() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
sum of logs of the ith entries of the arrays
that correspond to each multivariate sample
- getSumLog() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns the currently configured sum of logs implementation
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured sum of logs implementation
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured sum of logs implementation
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured sum of logs implementation
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured sum of logs implementation
- getSummary() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
- getSummary() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
- getSummary() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
- getSumOfCrossProducts() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of crossproducts, xi*yi.
- getSumOfLogs() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the sum of the logs of all the aggregated data.
- getSumOfLogs() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the sum of the logs of the values that have been added.
- getSumsq() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the sum of the squares of all the aggregated data.
- getSumsq() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the sum of the squares of the available values.
- getSumSq() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getSumSq() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
sum of squares of the ith entries of the arrays
that correspond to each multivariate sample
- getSumsq() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the sum of the squares of the values that have been added.
- getSumSq() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getSumsq() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the sum of the squares of the values that have been added.
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured sum of squares implementation.
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured sum of squares implementation
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured sum of squares implementation
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured sum of squares implementation
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured sum of squares implementation
- getSumSquaredErrors() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Returns the lower bound of the support for this distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Returns the lower bound of the support for this distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Returns the lower bound for the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Returns the upper bound of the support for this distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Returns the upper bound of the support for this distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Returns the upper bound for the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Returns the upper bound for the support of the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getT() - Method in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Returns the tridiagonal matrix T of the transform.
- getTheoreticalValue() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Get the theoretical value expected for this measurement
- getTiesStrategy() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
-
Return the TiesStrategy
- getTotalSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of squared deviations of the y values about their mean.
- getTrace() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTransformer(Class<?>) - Method in class org.apache.commons.math.util.TransformerMap
-
Returns the Transformer that is mapped to a class
if mapping is not present, this returns null.
- getTTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0
- getTwo() - Method in class org.apache.commons.math.dfp.Dfp
-
Get the constant 2.
- getTwo() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant 2.
- getU() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Returns the matrix U of the transform.
- getU() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Returns the matrix U of the decomposition.
- getU() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Returns the matrix U of the decomposition.
- getU() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Returns the matrix U of the decomposition.
- getU() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Returns the matrix U of the decomposition.
- getU() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the matrix U of the decomposition.
- getU() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the matrix U of the decomposition.
- getUnboundParameters() - Method in interface org.apache.commons.math.estimation.EstimationProblem
-
Deprecated.
Get the unbound parameters of the problem.
- getUnboundParameters() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Get the unbound parameters of the problem.
- getUniqueCount() - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values in the frequency table.
- getUnknownDistributionChiSquareTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0
- getUpperBounds() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Returns the array of upper bounds for the bins.
- getUpperBounds() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Returns a fresh copy of the array of upper bounds for the bins.
- getUpperDomain(int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Return the highest domain value for the given hypergeometric distribution
parameters.
- getUT() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the transpose of the matrix U of the decomposition.
- getUT() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the transpose of the matrix U of the decomposition.
- getV() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Returns the matrix V of the transform.
- getV() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the matrix V of the decomposition.
- getV() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the matrix V of the decomposition.
- getV() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the matrix V of the decomposition.
- getV() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the matrix V of the decomposition.
- getValue() - Method in class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
-
Get the value of the entry.
- getValue() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
-
Get the value of the entry.
- getValue() - Method in class org.apache.commons.math.linear.RealVector.Entry
-
Get the value of the entry.
- getValue() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
-
Get the value of the constraint (right hand side).
- getValue(double[]) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Compute the value of the linear equation at the current point
- getValue(RealVector) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Compute the value of the linear equation at the current point
- getValue() - Method in class org.apache.commons.math.optimization.RealPointValuePair
-
Get the value of the objective function.
- getValue() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Get the value of the objective function.
- getValue() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
-
Returns the value of the pair.
- getValueAtOptimum() - Method in class org.apache.commons.math.optimization.direct.PowellOptimizer.LineSearch
-
- getValueRef() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Get a reference to the value of the objective function.
- getValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the current set of values in an array of double primitives.
- getValues() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the current set of values in an array of double primitives.
- getValues() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
- getValuesFileURL() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for valuesFileURL
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the variance of the available values.
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the variance of the available values.
- getVariance() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the variance of the available values.
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the variance of the values that have been added.
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the variance of the values that have been added.
- getVarianceDirection() - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns the varianceDirection property.
- getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured variance implementation.
- getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured variance implementation
- getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured variance implementation
- getVT() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the transpose of the matrix V of the decomposition.
- getVT() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the transpose of the matrix V of the decomposition.
- getVT() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the transpose of the matrix V of the decomposition.
- getVT() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the transpose of the matrix V of the decomposition.
- getWeight() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Get the weight of the measurement in the least squares problem
- getWeight() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
-
Get the weight of the measurement in the fitting process.
- getWholeFormat() - Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
-
Access the whole format.
- getWholeFormat() - Method in class org.apache.commons.math.fraction.ProperFractionFormat
-
Access the whole format.
- getWidth() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get the width of the tableau.
- getWindowSize() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the maximum number of values that can be stored in the
dataset, or INFINITE_WINDOW (-1) if there is no limit.
- getWindowSize() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the maximum number of values that can be stored in the
dataset, or INFINITE_WINDOW (-1) if there is no limit.
- getX() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the abscissa of the vector.
- getX() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
-
Get the abscissa of the point.
- getXSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of squared deviations of the x values about their mean.
- getY() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the ordinate of the vector.
- getY() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
-
Get the observed value of the function at x.
- getZ() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the height of the vector.
- getZero() - Method in class org.apache.commons.math.complex.ComplexField
-
Get the additive identity of the field.
- getZero() - Method in class org.apache.commons.math.dfp.Dfp
-
Get the constant 0.
- getZero() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant 0.
- getZero() - Method in interface org.apache.commons.math.Field
-
Get the additive identity of the field.
- getZero() - Method in class org.apache.commons.math.fraction.BigFractionField
-
Get the additive identity of the field.
- getZero() - Method in class org.apache.commons.math.fraction.FractionField
-
Get the additive identity of the field.
- getZero() - Method in class org.apache.commons.math.util.BigRealField
-
Get the additive identity of the field.
- GillIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements the Gill fourth order Runge-Kutta
integrator for Ordinary Differential Equations .
- GillIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.GillIntegrator
-
Simple constructor.
- GillStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements a step interpolator for the Gill fourth
order Runge-Kutta integrator.
- GillStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
-
Simple constructor.
- GillStepInterpolator(GillStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
-
Copy constructor.
- globalCurrentTime - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
global current time
- globalPreviousTime - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
global previous time
- GLSMultipleLinearRegression - Class in org.apache.commons.math.stat.regression
-
The GLS implementation of the multiple linear regression.
- GLSMultipleLinearRegression() - Constructor for class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
- goal - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Deprecated.
- goal - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
- GoalType - Enum in org.apache.commons.math.optimization
-
Goal type for an optimization problem.
- GoalType() - Constructor for enum org.apache.commons.math.optimization.GoalType
-
- GOLD - Static variable in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Golden section.
- GOLDEN_SECTION - Static variable in class org.apache.commons.math.optimization.univariate.BrentOptimizer
-
Golden section.
- gradient() - Method in interface org.apache.commons.math.analysis.DifferentiableMultivariateRealFunction
-
Returns the gradient function.
- gradient(double, double[]) - Method in class org.apache.commons.math.optimization.fitting.HarmonicFitter.ParametricHarmonicFunction
-
Compute the gradient of the function with respect to its parameters.
- gradient(double, double[]) - Method in class org.apache.commons.math.optimization.fitting.ParametricGaussianFunction
-
Computes the gradient vector for a four variable version of the function
where the parameters, a, b, c, and d,
are considered the variables, not x.
- gradient(double, double[]) - Method in interface org.apache.commons.math.optimization.fitting.ParametricRealFunction
-
Compute the gradient of the function with respect to its parameters.
- gradient(double, double[]) - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter.ParametricPolynomial
-
Compute the gradient of the function with respect to its parameters.
- gradient - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Objective function gradient.
- gradientEvaluations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Number of gradient evaluations.
- GraggBulirschStoerIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements a Gragg-Bulirsch-Stoer integrator for
Ordinary Differential Equations.
- GraggBulirschStoerIntegrator(double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Simple constructor.
- GraggBulirschStoerIntegrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Simple constructor.
- GraggBulirschStoerStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements an interpolator for the Gragg-Bulirsch-Stoer
integrator.
- GraggBulirschStoerStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Simple constructor.
- GraggBulirschStoerStepInterpolator(double[], double[], double[], double[], double[][], boolean) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Simple constructor.
- GraggBulirschStoerStepInterpolator(GraggBulirschStoerStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Copy constructor.
- GREATER_THAN_TRAP - Static variable in class org.apache.commons.math.dfp.Dfp
-
Name for traps triggered by greaterThan.
- greaterThan(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Check if instance is greater than x.
- growLimit - Variable in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Factor for expanding the interval.
- growTable() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Grow the tables.
- growTable() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Grow the tables.
- guess() - Method in class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
-
Guesses the parameters based on the observed points.
- guess() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Estimate a first guess of the coefficients.
- guessAOmega() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Estimate a first guess of the a and ω coefficients.
- guessParametersErrors(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Guess the errors in unbound estimated parameters.
- guessParametersErrors(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
-
Deprecated.
Guess the errors in estimated parameters.
- guessParametersErrors() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Guess the errors in optimized parameters.
- guessPhi() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Estimate a first guess of the φ coefficient.
- I - Static variable in class org.apache.commons.math.complex.Complex
-
The square root of -1.
- i1 - Variable in class org.apache.commons.math.random.AbstractWell
-
Index indirection table giving for each index the value index + m1 taking table size into account.
- i2 - Variable in class org.apache.commons.math.random.AbstractWell
-
Index indirection table giving for each index the value index + m2 taking table size into account.
- i3 - Variable in class org.apache.commons.math.random.AbstractWell
-
Index indirection table giving for each index the value index + m3 taking table size into account.
- IDENTITY - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
The identity function.
- IDENTITY - Static variable in class org.apache.commons.math.geometry.Rotation
-
Identity rotation.
- identityPermutation(int) - Static method in class org.apache.commons.math.genetics.RandomKey
-
Generates a representation corresponding to an identity permutation of
length l which can be passed to the RandomKey constructor.
- ieeeFlags - Variable in class org.apache.commons.math.dfp.DfpField
-
IEEE 854-1987 signals.
- IEEEremainder(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Computes the remainder as prescribed by the IEEE 754 standard.
- ignored - Variable in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Ignore measurement indicator.
- illumination() - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
-
Get the illumination of the element.
- imagEigenvalues - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Imaginary part of the realEigenvalues.
- imagEigenvalues - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
-
Imaginary part of the realEigenvalues.
- imaginary - Variable in class org.apache.commons.math.complex.Complex
-
The imaginary part.
- imaginaryCharacter - Variable in class org.apache.commons.math.complex.ComplexFormat
-
The notation used to signify the imaginary part of the complex number.
- imaginaryFormat - Variable in class org.apache.commons.math.complex.ComplexFormat
-
The format used for the imaginary part.
- incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Determines whether or not this statistic can be incremented or cleared.
- incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Determines whether or not this statistic can be incremented or cleared.
- incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Determines whether or not this statistic can be incremented or cleared.
- incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Boolean test to determine if this Variance should also increment
the second moment, this evaluates to false when this Variance is
constructed with an external SecondMoment as a parameter.
- increasing - Variable in class org.apache.commons.math.ode.events.EventState
-
Variation direction around pending event.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Add a new vector to the sample.
- increment(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
-
Add a new vector to the sample.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Updates the internal state of the statistic to reflect the addition of the new value.
- increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Updates the internal state of the statistic to reflect the addition of the new value.
- incrementAll(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
- incrementAll(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
- incrementAll(double[]) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Updates the internal state of the statistic to reflect addition of
all values in the values array.
- incrementAll(double[], int, int) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Updates the internal state of the statistic to reflect addition of
the values in the designated portion of the values array.
- incrementIterationsCounter() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Increment the iterations counter by 1.
- incrementIterationsCounter() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Increment the iterations counter by 1.
- incrementIterationsCounter() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Increment the iterations counter by 1.
- incrementIterationsCounter() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Increment the iterations counter by 1.
- incrementIterationsCounter() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Increment the iterations counter by 1.
- incrementJacobianEvaluationsCounter() - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Increment the jacobian evaluations counter.
- index - Variable in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
Index of the wrong value.
- index - Variable in class org.apache.commons.math.linear.RealVector.Entry
-
Index of the entry.
- index - Variable in class org.apache.commons.math.ode.ContinuousOutputModel
-
Current interpolator index.
- index - Variable in class org.apache.commons.math.random.AbstractWell
-
Current index in the bytes pool.
- indicator(byte) - Static method in class org.apache.commons.math.util.MathUtils
-
For a byte value x, this method returns (byte)(+1) if x >= 0 and
(byte)(-1) if x < 0.
- indicator(double) - Static method in class org.apache.commons.math.util.MathUtils
-
For a double precision value x, this method returns +1.0 if x >= 0 and
-1.0 if x < 0.
- indicator(float) - Static method in class org.apache.commons.math.util.MathUtils
-
For a float value x, this method returns +1.0F if x >= 0 and -1.0F if x <
0.
- indicator(int) - Static method in class org.apache.commons.math.util.MathUtils
-
For an int value x, this method returns +1 if x >= 0 and -1 if x < 0.
- indicator(long) - Static method in class org.apache.commons.math.util.MathUtils
-
For a long value x, this method returns +1L if x >= 0 and -1L if x < 0.
- indicator(short) - Static method in class org.apache.commons.math.util.MathUtils
-
For a short value x, this method returns (short)(+1) if x >= 0 and
(short)(-1) if x < 0.
- inducedPermutation(List<S>, List<S>) - Static method in class org.apache.commons.math.genetics.RandomKey
-
Generates a representation of a permutation corresponding to a
permutation which yields permutedData when applied to
originalData.
- INF - Static variable in class org.apache.commons.math.complex.Complex
-
A complex number representing "+INF + INFi"
- INFINITE - Static variable in class org.apache.commons.math.dfp.Dfp
-
Indicator value for Infinity.
- INFINITE_WINDOW - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Represents an infinite window size.
- initialCapacity - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
The initial capacity of the array.
- initialization - Variable in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Initialization matrix for the higher order derivatives wrt y'', y''' ...
- initializeArrays() - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Initialize the integrator internal arrays.
- initializeColumnLabels() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Initialize the labels for the columns.
- initialized - Variable in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Initialization indicator.
- initializeEstimate(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Initialization of the common parts of the estimation.
- initializeHighOrderDerivatives(double[], double[][]) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Initialize the high order scaled derivatives at step start.
- initializeHighOrderDerivatives(double[], double[][]) - Method in interface org.apache.commons.math.ode.MultistepIntegrator.NordsieckTransformer
-
Initialize the high order scaled derivatives at step start.
- initializeHighOrderDerivatives(double[], double[][]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
-
Initialize the high order scaled derivatives at step start.
- initializeHighOrderDerivatives(double[], double[][]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Initialize the high order scaled derivatives at step start.
- initializeStep(FirstOrderDifferentialEquations, boolean, int, double[], double, double[], double[], double[], double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Initialize the integration step.
- initialStep - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
User supplied initial step.
- initialStep - Variable in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
Initial step used to bracket the optimum in line search.
- initialStepBoundFactor - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Positive input variable used in determining the initial step bound.
- initialStepBoundFactor - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Positive input variable used in determining the initial step bound.
- initialTime - Variable in class org.apache.commons.math.ode.ContinuousOutputModel
-
Initial integration time.
- innerCumulativeProbability(int, int, int, int, int, int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
For this distribution, X, this method returns P(x0 ≤ X ≤ x1).
- inputArray - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl.ArrayDataAdapter
-
Array of input data values
- inputStream - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl.StreamDataAdapter
-
Input stream providing access to the data
- insertionSort(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Sort in place a (small) array slice using insertion sort
- INSTANCE - Static variable in class org.apache.commons.math.complex.ComplexField.LazyHolder
-
Cached field instance.
- INSTANCE - Static variable in class org.apache.commons.math.fraction.BigFractionField.LazyHolder
-
Cached field instance.
- INSTANCE - Static variable in class org.apache.commons.math.fraction.FractionField.LazyHolder
-
Cached field instance.
- INSTANCE - Static variable in class org.apache.commons.math.ode.sampling.DummyStepHandler.LazyHolder
-
Cached field instance.
- INSTANCE - Static variable in class org.apache.commons.math.util.BigRealField.LazyHolder
-
Cached field instance.
- IntegerDistribution - Interface in org.apache.commons.math.distribution
-
Interface for discrete distributions of integer-valued random variables.
- integrate(double, double) - Method in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
-
Deprecated.
- integrate(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
-
Integrate the function in the given interval.
- integrate(double, double) - Method in class org.apache.commons.math.analysis.integration.RombergIntegrator
-
Deprecated.
- integrate(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.integration.RombergIntegrator
-
Integrate the function in the given interval.
- integrate(double, double) - Method in class org.apache.commons.math.analysis.integration.SimpsonIntegrator
-
Deprecated.
- integrate(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.integration.SimpsonIntegrator
-
Integrate the function in the given interval.
- integrate(double, double) - Method in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
-
Deprecated.
- integrate(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
-
Integrate the function in the given interval.
- integrate(double, double) - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
-
- integrate(UnivariateRealFunction, double, double) - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
-
Integrate the function in the given interval.
- integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in interface org.apache.commons.math.ode.FirstOrderIntegrator
-
Integrate the differential equations up to the given time.
- integrate(double, double[], double[][], double, double[], double[][], double[][]) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Integrate the differential equations and the variational equations up to the given time.
- integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
-
Integrate the differential equations up to the given time.
- integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
-
Integrate the differential equations up to the given time.
- integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
-
Integrate the differential equations up to the given time.
- integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Integrate the differential equations up to the given time.
- integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Integrate the differential equations up to the given time.
- integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Integrate the differential equations up to the given time.
- integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
-
Integrate the differential equations up to the given time.
- integrate(SecondOrderDifferentialEquations, double, double[], double[], double, double[], double[]) - Method in interface org.apache.commons.math.ode.SecondOrderIntegrator
-
Integrate the differential equations up to the given time
- integrator - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Underlying integrator for compound problem.
- integrator - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaStepInterpolator
-
Reference to the integrator.
- IntegratorException - Exception in org.apache.commons.math.ode
-
This exception is made available to users to report
the error conditions that are triggered during integration
- IntegratorException(String, Object...) - Constructor for exception org.apache.commons.math.ode.IntegratorException
-
- IntegratorException(Localizable, Object...) - Constructor for exception org.apache.commons.math.ode.IntegratorException
-
Simple constructor.
- IntegratorException(Throwable) - Constructor for exception org.apache.commons.math.ode.IntegratorException
-
Create an exception with a given root cause.
- internalArray - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
The internal storage array.
- interpolate(double[], double[], double[][]) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[], double[][]) - Method in interface org.apache.commons.math.analysis.interpolation.BivariateRealGridInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LinearInterpolator
-
Computes a linear interpolating function for the data set.
- interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
Compute an interpolating function by performing a loess fit
on the data at the original abscissae and then building a cubic spline
with a
SplineInterpolator
on the resulting fit.
- interpolate(double[][], double[]) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[][], double[]) - Method in interface org.apache.commons.math.analysis.interpolation.MultivariateRealInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.NevilleInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[], double[][]) - Method in class org.apache.commons.math.analysis.interpolation.SmoothingBicubicSplineInterpolator
-
Deprecated.
Computes an interpolating function for the data set.
- interpolate(double[], double[], double[][]) - Method in class org.apache.commons.math.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.SplineInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[], double[], double[][][]) - Method in class org.apache.commons.math.analysis.interpolation.TricubicSplineInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[], double[], double[][][]) - Method in interface org.apache.commons.math.analysis.interpolation.TrivariateRealGridInterpolator
-
Computes an interpolating function for the data set.
- interpolate(double[], double[]) - Method in interface org.apache.commons.math.analysis.interpolation.UnivariateRealInterpolator
-
Computes an interpolating function for the data set.
- interpolatedDerivatives - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
interpolated derivatives
- interpolatedState - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
interpolated state
- interpolatedTime - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
interpolated time
- interpolateXAtY(WeightedObservedPoint[], int, int, double) - Method in class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
-
Interpolates using the specified points to determine X at the specified
Y.
- interpolator - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Wrapped interpolator.
- intValue() - Method in class org.apache.commons.math.dfp.Dfp
-
Convert this to an integer.
- intValue() - Method in class org.apache.commons.math.fraction.BigFraction
-
Gets the fraction as an int.
- intValue() - Method in class org.apache.commons.math.fraction.Fraction
-
Gets the fraction as an int.
- invalidateParameterDependentMoments() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Invalidates the cached mean and variance.
- InvalidMatrixException - Exception in org.apache.commons.math.linear
-
Thrown when a system attempts an operation on a matrix, and
that matrix does not satisfy the preconditions for the
aforementioned operation.
- InvalidMatrixException(String, Object...) - Constructor for exception org.apache.commons.math.linear.InvalidMatrixException
-
- InvalidMatrixException(Localizable, Object...) - Constructor for exception org.apache.commons.math.linear.InvalidMatrixException
-
Construct an exception with the given message.
- InvalidMatrixException(Throwable) - Constructor for exception org.apache.commons.math.linear.InvalidMatrixException
-
Construct an exception with the given message.
- InvalidRepresentationException - Exception in org.apache.commons.math.genetics
-
Exception indicating that the representation of a chromosome is not valid.
- InvalidRepresentationException() - Constructor for exception org.apache.commons.math.genetics.InvalidRepresentationException
-
Constructor
- InvalidRepresentationException(String) - Constructor for exception org.apache.commons.math.genetics.InvalidRepresentationException
-
Construct an InvalidRepresentationException
- InvalidRepresentationException(Throwable) - Constructor for exception org.apache.commons.math.genetics.InvalidRepresentationException
-
Construct an InvalidRepresentationException
- InvalidRepresentationException(String, Throwable) - Constructor for exception org.apache.commons.math.genetics.InvalidRepresentationException
-
Construct an InvalidRepresentationException
- inverse() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Deprecated.
- inverse() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the inverse of this matrix.
- inverse() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the inverse matrix if this matrix is invertible.
- inverse() - Method in interface org.apache.commons.math.linear.RealMatrix
-
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns the largest x, such
that P(X ≤ x) ≤ p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
For this distribution, X, this method returns the largest x, such that
P(X ≤ x) ≤ p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.ContinuousDistribution
-
For this distribution, X, this method returns x such that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
-
For this distribution, X, this method returns the largest x such that
P(X ≤ x) <= p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
For this distribution, X, this method returns the largest x, such that
P(X ≤ x) ≤ p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
For this distribution, X, this method returns the critical point x, such
that P(X < x) = p.
- inversetransform(double[]) - Method in class org.apache.commons.math.transform.FastCosineTransformer
-
Inversely transform the given real data set.
- inversetransform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastCosineTransformer
-
Inversely transform the given real function, sampled on the given interval.
- inversetransform(double[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
-
Inversely transform the given real data set.
- inversetransform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastFourierTransformer
-
Inversely transform the given real function, sampled on the given interval.
- inversetransform(Complex[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
-
Inversely transform the given complex data set.
- inversetransform(double[]) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
-
Inversely transform the given real data set.
- inversetransform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastHadamardTransformer
-
Inversely transform the given real function, sampled on the given interval.
- inversetransform(double[]) - Method in class org.apache.commons.math.transform.FastSineTransformer
-
Inversely transform the given real data set.
- inversetransform(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastSineTransformer
-
Inversely transform the given real function, sampled on the given interval.
- inversetransform(double[]) - Method in interface org.apache.commons.math.transform.RealTransformer
-
Inversely transform the given real data set.
- inversetransform(UnivariateRealFunction, double, double, int) - Method in interface org.apache.commons.math.transform.RealTransformer
-
Inversely transform the given real function, sampled on the given interval.
- inversetransform2(double[]) - Method in class org.apache.commons.math.transform.FastCosineTransformer
-
Inversely transform the given real data set.
- inversetransform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastCosineTransformer
-
Inversely transform the given real function, sampled on the given interval.
- inversetransform2(double[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
-
Inversely transform the given real data set.
- inversetransform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastFourierTransformer
-
Inversely transform the given real function, sampled on the given interval.
- inversetransform2(Complex[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
-
Inversely transform the given complex data set.
- inversetransform2(double[]) - Method in class org.apache.commons.math.transform.FastSineTransformer
-
Inversely transform the given real data set.
- inversetransform2(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.transform.FastSineTransformer
-
Inversely transform the given real function, sampled on the given interval.
- INVERT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- iRm1 - Variable in class org.apache.commons.math.random.AbstractWell
-
Index indirection table giving for each index its predecessor taking table size into account.
- iRm2 - Variable in class org.apache.commons.math.random.AbstractWell
-
Index indirection table giving for each index its second predecessor taking table size into account.
- isBetween(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
-
Determines whether a value is between two other values.
- isBiasCorrected() - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns true iff biasCorrected property is set to true.
- isBiasCorrected() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
- isBiasCorrected - Variable in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Determines whether or not bias correction is applied when computing the
value of the statisic.
- isBiasCorrected() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
- isBiasCorrected - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Indicator for bias correction.
- isBound() - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Check if the parameter is bound
- isBracketing(double, double, UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Returns true iff the function takes opposite signs at the endpoints.
- isDefaultValue(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Determine if this value is within epsilon of zero.
- isEmpty() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Check if the manager does not manage any event handlers.
- isForward() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Check if the natural integration direction is forward.
- isForward() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Check if the natural integration direction is forward.
- isForward() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Check if the natural integration direction is forward.
- isForward() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Check if the natural integration direction is forward.
- isForward - Variable in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
-
Forward/reverse indicator.
- isForward() - Method in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
-
Check if computation has been done for forward or reverse transform.
- isIgnored() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Check if this measurement should be ignored
- isInfinite - Variable in class org.apache.commons.math.complex.Complex
-
Record whether this complex number is infinite.
- isInfinite() - Method in class org.apache.commons.math.complex.Complex
-
Returns true if either the real or imaginary part of this complex number
takes an infinite value (either Double.POSITIVE_INFINITY or
Double.NEGATIVE_INFINITY) and neither part
is NaN.
- isInfinite() - Method in class org.apache.commons.math.dfp.Dfp
-
Check if instance is infinite.
- isInfinite() - Method in class org.apache.commons.math.geometry.Vector3D
-
Returns true if any coordinate of this vector is infinite and none are NaN;
false otherwise
- isInfinite() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns true if any coordinate of this vector is infinite and none are NaN;
false otherwise
- isInfinite() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Check whether any coordinate of this vector is infinite and none are NaN.
- isInfinite() - Method in interface org.apache.commons.math.linear.RealVector
-
Check whether any coordinate of this vector is infinite and none are NaN.
- isLastStep - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Indicator for last step.
- isLoaded() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Property indicating whether or not the distribution has been loaded.
- isLoaded() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Property indicating whether or not the distribution has been loaded.
- isNaN - Variable in class org.apache.commons.math.complex.Complex
-
Record whether this complex number is equal to NaN.
- isNaN() - Method in class org.apache.commons.math.complex.Complex
-
Returns true if either or both parts of this complex number is NaN;
false otherwise
- isNaN() - Method in class org.apache.commons.math.dfp.Dfp
-
Check if instance is not a number.
- isNaN() - Method in class org.apache.commons.math.geometry.Vector3D
-
Returns true if any coordinate of this vector is NaN; false otherwise
- isNaN() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns true if any coordinate of this vector is NaN; false otherwise
- isNaN() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Check whether any coordinate of this vector is NaN.
- isNaN() - Method in interface org.apache.commons.math.linear.RealVector
-
Check whether any coordinate of this vector is NaN.
- isNoIntercept() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
- isNonSingular() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
-
Check if the decomposed matrix is non-singular.
- isNonSingular() - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Check if the decomposed matrix is non-singular.
- isNonSingular() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
-
Check if the decomposed matrix is non-singular.
- isNonSingular() - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Check if the decomposed matrix is non-singular.
- isNonSingular() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
-
Check if the decomposed matrix is non-singular.
- isNonSingular() - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
-
Check if the decomposed matrix is non-singular.
- isNonSingular() - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
-
Check if the decomposed matrix is non-singular.
- isNonSingular() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
-
Check if the decomposed matrix is non-singular.
- isOptimal() - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Returns whether the problem is at an optimal state.
- isPowerOf2(long) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
-
Returns true if the argument is power of 2.
- isRootOK(double, double, Complex) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Returns true iff the given complex root is actually a real zero
in the given interval, within the solver tolerance level.
- isSame(Chromosome) - Method in class org.apache.commons.math.genetics.BinaryChromosome
-
Returns true iff another has the same
representation and therefore the same fitness.
- isSame(Chromosome) - Method in class org.apache.commons.math.genetics.Chromosome
-
Returns true iff another has the same
representation and therefore the same fitness.
- isSame(Chromosome) - Method in class org.apache.commons.math.genetics.RandomKey
-
Returns true iff another is a RandomKey and
encodes the same permutation.
- isSatisfied(Population) - Method in class org.apache.commons.math.genetics.FixedGenerationCount
-
Determine whether or not the given number of generations have passed.
- isSatisfied(Population) - Method in interface org.apache.commons.math.genetics.StoppingCondition
-
Determine whether or not the given population satisfies the stopping
condition.
- isSequence(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Returns true if the arguments form a (strictly) increasing sequence
- isSingular() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Deprecated.
- isSingular() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Is this a singular matrix?
- isSingular() - Method in interface org.apache.commons.math.linear.RealMatrix
-
- isSquare() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Is this a square matrix?
- isSquare() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Is this a square matrix?
- isSquare() - Method in interface org.apache.commons.math.linear.AnyMatrix
-
Is this a square matrix?
- isSquare() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Is this a square matrix?
- isStrictlyIncreasing(double[]) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
-
Determines if the given array is ordered in a strictly increasing
fashion.
- isSupportLowerBoundInclusive() - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Use this method to get information about whether the lower bound
of the support is inclusive or not.
- isSupportUpperBoundInclusive() - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Use this method to get information about whether the upper bound
of the support is inclusive or not.
- isSymmetric(RealMatrix) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Check if a matrix is symmetric.
- isUpperBiDiagonal() - Method in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Check if the matrix is transformed to upper bi-diagonal.
- iter - Variable in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
-
Iterator pointing to the entry.
- iter - Variable in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
-
Underlying iterator.
- iterateSimplex(Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Compute the next simplex of the algorithm.
- iterateSimplex(Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.MultiDirectional
-
Compute the next simplex of the algorithm.
- iterateSimplex(Comparator<RealPointValuePair>) - Method in class org.apache.commons.math.optimization.direct.NelderMead
-
Compute the next simplex of the algorithm.
- iterationCount - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
The last iteration count.
- iterations - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Number of iterations already performed.
- iterations - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Number of iterations already performed.
- iterations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Number of iterations already performed.
- iterations - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Number of iterations already performed.
- iterations - Variable in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Number of iterations.
- iterator() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Chromosome list iterator
- iterator() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Generic dense iterator.
- iterator() - Method in interface org.apache.commons.math.linear.RealVector
-
Generic dense iterator.
- iterator() - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Create an iterator over this counter.
- iterator() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Get an iterator over map elements.
- iterator() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Get an iterator over map elements.
- m - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Number of rows of the initial matrix.
- M - Static variable in class org.apache.commons.math.random.MersenneTwister
-
Period second parameter.
- M1 - Static variable in class org.apache.commons.math.random.Well1024a
-
First parameter of the algorithm.
- M1 - Static variable in class org.apache.commons.math.random.Well19937a
-
First parameter of the algorithm.
- M1 - Static variable in class org.apache.commons.math.random.Well19937c
-
First parameter of the algorithm.
- M1 - Static variable in class org.apache.commons.math.random.Well44497a
-
First parameter of the algorithm.
- M1 - Static variable in class org.apache.commons.math.random.Well44497b
-
First parameter of the algorithm.
- M1 - Static variable in class org.apache.commons.math.random.Well512a
-
First parameter of the algorithm.
- m1 - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
First moment of values that have been added
- M2 - Static variable in class org.apache.commons.math.random.Well1024a
-
Second parameter of the algorithm.
- M2 - Static variable in class org.apache.commons.math.random.Well19937a
-
Second parameter of the algorithm.
- M2 - Static variable in class org.apache.commons.math.random.Well19937c
-
Second parameter of the algorithm.
- M2 - Static variable in class org.apache.commons.math.random.Well44497a
-
Second parameter of the algorithm.
- M2 - Static variable in class org.apache.commons.math.random.Well44497b
-
Second parameter of the algorithm.
- M2 - Static variable in class org.apache.commons.math.random.Well512a
-
Second parameter of the algorithm.
- m2 - Variable in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
second moment of values that have been added
- M3 - Static variable in class org.apache.commons.math.random.Well1024a
-
Third parameter of the algorithm.
- M3 - Static variable in class org.apache.commons.math.random.Well19937a
-
Third parameter of the algorithm.
- M3 - Static variable in class org.apache.commons.math.random.Well19937c
-
Third parameter of the algorithm.
- M3 - Static variable in class org.apache.commons.math.random.Well44497a
-
Third parameter of the algorithm.
- M3 - Static variable in class org.apache.commons.math.random.Well44497b
-
Third parameter of the algorithm.
- M3 - Static variable in class org.apache.commons.math.random.Well512a
-
Third parameter of the algorithm.
- m3 - Variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
third moment of values that have been added
- m4 - Variable in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
fourth moment of values that have been added
- MAG01 - Static variable in class org.apache.commons.math.random.MersenneTwister
-
X * MATRIX_A for X = {0, 1}.
- main - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Main diagonal.
- main - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Main diagonal of the tridiagonal matrix.
- main - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Main diagonal.
- mainSetDimension - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Main set dimension.
- mant - Variable in class org.apache.commons.math.dfp.Dfp
-
Mantissa.
- map(UnivariateRealFunction) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Acts as if implemented as:
- map(UnivariateRealFunction) - Method in interface org.apache.commons.math.linear.RealVector
-
Acts as if implemented as:
- map - Variable in class org.apache.commons.math.util.TransformerMap
-
The internal Map.
- mapAbs() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.abs(double) function to each entry.
- mapAbs() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapAbsToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.abs(double) function to each entry.
- mapAbsToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.abs(double) function to each entry.
- mapAbsToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapAcos() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.acos(double) function to each entry.
- mapAcos() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapAcosToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.acos(double) function to each entry.
- mapAcosToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.acos(double) function to each entry.
- mapAcosToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapAdd(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Add a value to each entry.
- mapAdd(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map an addition operation to each entry.
- mapAdd(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Map an addition operation to each entry.
- mapAdd(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Add a value to each entry.
- mapAdd(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Add a value to each entry.
- mapAdd(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map an addition operation to each entry.
- mapAddToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Add a value to each entry.
- mapAddToSelf(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map an addition operation to each entry.
- mapAddToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Add a value to each entry.
- mapAddToSelf(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Map an addition operation to each entry.
- mapAddToSelf(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Add a value to each entry.
- mapAddToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Add a value to each entry.
- mapAddToSelf(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map an addition operation to each entry.
- mapAsin() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.asin(double) function to each entry.
- mapAsin() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapAsinToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.asin(double) function to each entry.
- mapAsinToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.asin(double) function to each entry.
- mapAsinToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapAtan() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.atan(double) function to each entry.
- mapAtan() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapAtanToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.atan(double) function to each entry.
- mapAtanToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.atan(double) function to each entry.
- mapAtanToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapCbrt() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.cbrt(double) function to each entry.
- mapCbrt() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapCbrtToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.cbrt(double) function to each entry.
- mapCbrtToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.cbrt(double) function to each entry.
- mapCbrtToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapCeil() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.ceil(double) function to each entry.
- mapCeil() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapCeilToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.ceil(double) function to each entry.
- mapCeilToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.ceil(double) function to each entry.
- mapCeilToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapCos() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.cos(double) function to each entry.
- mapCos() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapCosh() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.cosh(double) function to each entry.
- mapCosh() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapCoshToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.cosh(double) function to each entry.
- mapCoshToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.cosh(double) function to each entry.
- mapCoshToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapCosToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.cos(double) function to each entry.
- mapCosToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.cos(double) function to each entry.
- mapCosToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapDivide(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Divide each entry.
- mapDivide(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map a division operation to each entry.
- mapDivide(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Map a division operation to each entry.
- mapDivide(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Divide each entry.
- mapDivide(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map a division operation to each entry.
- mapDivideToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Divide each entry.
- mapDivideToSelf(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map a division operation to each entry.
- mapDivideToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Divide each entry.
- mapDivideToSelf(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Map a division operation to each entry.
- mapDivideToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Divide each entry.
- mapDivideToSelf(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map a division operation to each entry.
- mapExp() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.exp(double) function to each entry.
- mapExp() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapExpm1() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.expm1(double) function to each entry.
- mapExpm1() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapExpm1ToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.expm1(double) function to each entry.
- mapExpm1ToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.expm1(double) function to each entry.
- mapExpm1ToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapExpToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map Math.exp(double) operation to each entry.
- mapExpToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map Math.exp(double) operation to each entry.
- mapExpToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapFloor() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.floor(double) function to each entry.
- mapFloor() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapFloorToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.floor(double) function to each entry.
- mapFloorToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.floor(double) function to each entry.
- mapFloorToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapInv() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the 1/x function to each entry.
- mapInv() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map the 1/x function to each entry.
- mapInv() - Method in interface org.apache.commons.math.linear.FieldVector
-
Map the 1/x function to each entry.
- mapInv() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapInv() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map the 1/x function to each entry.
- mapInvToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the 1/x function to each entry.
- mapInvToSelf() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map the 1/x function to each entry.
- mapInvToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the 1/x function to each entry.
- mapInvToSelf() - Method in interface org.apache.commons.math.linear.FieldVector
-
Map the 1/x function to each entry.
- mapInvToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapInvToSelf() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map the 1/x function to each entry.
- mapLog() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.log(double) function to each entry.
- mapLog() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapLog10() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.log10(double) function to each entry.
- mapLog10() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapLog10ToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.log10(double) function to each entry.
- mapLog10ToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.log10(double) function to each entry.
- mapLog10ToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapLog1p() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.log1p(double) function to each entry.
- mapLog1p() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapLog1pToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.log1p(double) function to each entry.
- mapLog1pToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.log1p(double) function to each entry.
- mapLog1pToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapLogToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.log(double) function to each entry.
- mapLogToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.log(double) function to each entry.
- mapLogToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapMultiply(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Multiply each entry.
- mapMultiply(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map a multiplication operation to each entry.
- mapMultiply(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Map a multiplication operation to each entry.
- mapMultiply(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Multiply each entry.
- mapMultiply(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map a multiplication operation to each entry.
- mapMultiplyToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Multiply each entry.
- mapMultiplyToSelf(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map a multiplication operation to each entry.
- mapMultiplyToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Multiply each entry.
- mapMultiplyToSelf(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Map a multiplication operation to each entry.
- mapMultiplyToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Multiply each entry.
- mapMultiplyToSelf(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map a multiplication operation to each entry.
- mapPow(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map a power operation to each entry.
- mapPow(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapPowToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map a power operation to each entry.
- mapPowToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map a power operation to each entry.
- mapPowToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapRint() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.rint(double) function to each entry.
- mapRint() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapRintToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.rint(double) function to each entry.
- mapRintToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.rint(double) function to each entry.
- mapRintToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSignum() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.signum(double) function to each entry.
- mapSignum() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSignumToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.signum(double) function to each entry.
- mapSignumToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.signum(double) function to each entry.
- mapSignumToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSin() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.sin(double) function to each entry.
- mapSin() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSinh() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.sinh(double) function to each entry.
- mapSinh() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSinhToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.sinh(double) function to each entry.
- mapSinhToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.sinh(double) function to each entry.
- mapSinhToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSinToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.sin(double) function to each entry.
- mapSinToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.sin(double) function to each entry.
- mapSinToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSqrt() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.sqrt(double) function to each entry.
- mapSqrt() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSqrtToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.sqrt(double) function to each entry.
- mapSqrtToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.sqrt(double) function to each entry.
- mapSqrtToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapSubtract(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Subtract a value from each entry.
- mapSubtract(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map a subtraction operation to each entry.
- mapSubtract(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Map a subtraction operation to each entry.
- mapSubtract(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Subtract a value from each entry.
- mapSubtract(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map a subtraction operation to each entry.
- mapSubtractToSelf(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Subtract a value from each entry.
- mapSubtractToSelf(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Map a subtraction operation to each entry.
- mapSubtractToSelf(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Subtract a value from each entry.
- mapSubtractToSelf(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Map a subtraction operation to each entry.
- mapSubtractToSelf(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Subtract a value from each entry.
- mapSubtractToSelf(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Map a subtraction operation to each entry.
- mapTan() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.tan(double) function to each entry.
- mapTan() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapTanh() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.tanh(double) function to each entry.
- mapTanh() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapTanhToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.tanh(double) function to each entry.
- mapTanhToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.tanh(double) function to each entry.
- mapTanhToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapTanToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.tan(double) function to each entry.
- mapTanToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.tan(double) function to each entry.
- mapTanToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapToSelf(UnivariateRealFunction) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Acts as if it is implemented as:
- mapToSelf(UnivariateRealFunction) - Method in interface org.apache.commons.math.linear.RealVector
-
Acts as if it is implemented as:
- mapUlp() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.ulp(double) function to each entry.
- mapUlp() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mapUlpToSelf() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Map the Math.ulp(double) function to each entry.
- mapUlpToSelf() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Map the Math.ulp(double) function to each entry.
- mapUlpToSelf() - Method in interface org.apache.commons.math.linear.RealVector
-
Deprecated.
in 2.2 (to be removed in 3.0).
- mask - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Bit mask for hash values.
- mask - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Bit mask for hash values.
- MASK_30BITS - Static variable in class org.apache.commons.math.util.FastMath
-
Mask used to clear low order 30 bits
- MathConfigurationException - Exception in org.apache.commons.math
-
Signals a configuration problem with any of the factory methods.
- MathConfigurationException() - Constructor for exception org.apache.commons.math.MathConfigurationException
-
Default constructor.
- MathConfigurationException(String, Object...) - Constructor for exception org.apache.commons.math.MathConfigurationException
-
Constructs an exception with specified formatted detail message.
- MathConfigurationException(Localizable, Object...) - Constructor for exception org.apache.commons.math.MathConfigurationException
-
Constructs an exception with specified formatted detail message.
- MathConfigurationException(Throwable) - Constructor for exception org.apache.commons.math.MathConfigurationException
-
Create an exception with a given root cause.
- MathConfigurationException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.MathConfigurationException
-
Constructs an exception with specified formatted detail message and root cause.
- MathConfigurationException(Throwable, Localizable, Object...) - Constructor for exception org.apache.commons.math.MathConfigurationException
-
Constructs an exception with specified formatted detail message and root cause.
- MathException - Exception in org.apache.commons.math
-
Base class for commons-math checked exceptions.
- MathException() - Constructor for exception org.apache.commons.math.MathException
-
Constructs a new MathException with no
detail message.
- MathException(String, Object...) - Constructor for exception org.apache.commons.math.MathException
-
- MathException(Localizable, Object...) - Constructor for exception org.apache.commons.math.MathException
-
Constructs a new MathException with specified
formatted detail message.
- MathException(Throwable) - Constructor for exception org.apache.commons.math.MathException
-
Constructs a new MathException with specified
nested Throwable root cause.
- MathException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.MathException
-
- MathException(Throwable, Localizable, Object...) - Constructor for exception org.apache.commons.math.MathException
-
Constructs a new MathException with specified
formatted detail message and nested Throwable root cause.
- MathIllegalArgumentException - Exception in org.apache.commons.math.exception
-
Base class for all preconditions violation exceptions.
- MathIllegalArgumentException(Localizable, Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.MathIllegalArgumentException
-
- MathIllegalArgumentException(Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.MathIllegalArgumentException
-
- MathIllegalNumberException - Exception in org.apache.commons.math.exception
-
Base class for exceptions raised by a wrong number.
- MathIllegalNumberException(Localizable, Localizable, Number, Object...) - Constructor for exception org.apache.commons.math.exception.MathIllegalNumberException
-
Construct an exception.
- MathIllegalNumberException(Localizable, Number, Object...) - Constructor for exception org.apache.commons.math.exception.MathIllegalNumberException
-
Construct an exception.
- MathIllegalStateException - Exception in org.apache.commons.math.exception
-
Base class for all exceptions that signal a mismatch between the
current state and the user's expectations.
- MathIllegalStateException(Localizable, Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.MathIllegalStateException
-
Simple constructor.
- MathIllegalStateException(Throwable, Localizable, Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.MathIllegalStateException
-
Simple constructor.
- MathIllegalStateException(Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.MathIllegalStateException
-
- MathIllegalStateException(Throwable, Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.MathIllegalStateException
-
Simple constructor.
- MathInternalError - Exception in org.apache.commons.math.exception
-
Exception triggered when something that shouldn't happen does happen.
- MathInternalError() - Constructor for exception org.apache.commons.math.exception.MathInternalError
-
Simple constructor.
- MathInternalError(Throwable) - Constructor for exception org.apache.commons.math.exception.MathInternalError
-
Simple constructor.
- MathRuntimeException - Exception in org.apache.commons.math
-
Base class for commons-math unchecked exceptions.
- MathRuntimeException(String, Object...) - Constructor for exception org.apache.commons.math.MathRuntimeException
-
- MathRuntimeException(Localizable, Object...) - Constructor for exception org.apache.commons.math.MathRuntimeException
-
Constructs a new MathRuntimeException with specified
formatted detail message.
- MathRuntimeException(Throwable) - Constructor for exception org.apache.commons.math.MathRuntimeException
-
Constructs a new MathRuntimeException with specified
nested Throwable root cause.
- MathRuntimeException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.MathRuntimeException
-
- MathRuntimeException(Throwable, Localizable, Object...) - Constructor for exception org.apache.commons.math.MathRuntimeException
-
Constructs a new MathRuntimeException with specified
formatted detail message and nested Throwable root cause.
- MathThrowable - Interface in org.apache.commons.math.exception
-
Interface for commons-math throwables.
- MathUnsupportedOperationException - Exception in org.apache.commons.math.exception
-
Base class for all unsupported features.
- MathUnsupportedOperationException(Object...) - Constructor for exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
- MathUnsupportedOperationException(Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
- MathUtils - Class in org.apache.commons.math.util
-
Some useful additions to the built-in functions in Math.
- MathUtils() - Constructor for class org.apache.commons.math.util.MathUtils
-
Private Constructor
- MathUtils.OrderDirection - Enum in org.apache.commons.math.util
-
Specification of ordering direction.
- MathUtils.OrderDirection() - Constructor for enum org.apache.commons.math.util.MathUtils.OrderDirection
-
- MatrixIndexException - Exception in org.apache.commons.math.linear
-
Thrown when an operation addresses a matrix coordinate (row, col)
which is outside of the dimensions of a matrix.
- MatrixIndexException(String, Object...) - Constructor for exception org.apache.commons.math.linear.MatrixIndexException
-
- MatrixIndexException(Localizable, Object...) - Constructor for exception org.apache.commons.math.linear.MatrixIndexException
-
Constructs a new instance with specified formatted detail message.
- MatrixUtils - Class in org.apache.commons.math.linear
-
A collection of static methods that operate on or return matrices.
- MatrixUtils() - Constructor for class org.apache.commons.math.linear.MatrixUtils
-
Private constructor.
- MatrixUtils.BigFractionMatrixConverter - Class in org.apache.commons.math.linear
-
- MatrixUtils.BigFractionMatrixConverter() - Constructor for class org.apache.commons.math.linear.MatrixUtils.BigFractionMatrixConverter
-
Simple constructor.
- MatrixUtils.FractionMatrixConverter - Class in org.apache.commons.math.linear
-
- MatrixUtils.FractionMatrixConverter() - Constructor for class org.apache.commons.math.linear.MatrixUtils.FractionMatrixConverter
-
Simple constructor.
- MatrixVisitorException - Exception in org.apache.commons.math.linear
-
Thrown when a visitor encounters an error while processing a matrix entry.
- MatrixVisitorException(String, Object[]) - Constructor for exception org.apache.commons.math.linear.MatrixVisitorException
-
Constructs a new instance with specified formatted detail message.
- MatrixVisitorException(Localizable, Object[]) - Constructor for exception org.apache.commons.math.linear.MatrixVisitorException
-
Constructs a new instance with specified formatted detail message.
- max - Variable in exception org.apache.commons.math.exception.NumberIsTooLargeException
-
Higher bound.
- max - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Max loaded value
- Max - Class in org.apache.commons.math.stat.descriptive.rank
-
Returns the maximum of the available values.
- Max() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Max
-
Create a Max instance
- Max(Max) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Max
-
Copy constructor, creates a new Max identical
to the original
- max - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
The maximum value
- max - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
max of values that have been added
- MAX - Static variable in class org.apache.commons.math.stat.StatUtils
-
max
- max(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the maximum of the entries in the input array, or
Double.NaN if the array is empty.
- max(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the maximum of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- max(int, int) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the maximum of two values
- max(long, long) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the maximum of two values
- max(float, float) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the maximum of two values
- max(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the maximum of two values
- MAX_CACHED_LEVELS - Static variable in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Maximum number of partitioning pivots cached (each level double the number of pivots).
- MAX_EXP - Static variable in class org.apache.commons.math.dfp.Dfp
-
The maximum exponent before overflow is signaled and results flushed
to infinity
- maxCheckInterval - Variable in class org.apache.commons.math.ode.events.EventState
-
Maximal time interval between events handler checks.
- maxChecks - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
maximal number of checks for each iteration.
- maxCostEval - Variable in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Maximal allowed number of cost evaluations.
- maxEvaluations - Variable in exception org.apache.commons.math.MaxEvaluationsExceededException
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Maximal number of evaluations allowed.
- maxEvaluations - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Maximal number of evaluations allowed.
- MaxEvaluationsExceededException - Exception in org.apache.commons.math
-
Error thrown when a numerical computation exceeds its allowed
number of functions evaluations.
- MaxEvaluationsExceededException(int) - Constructor for exception org.apache.commons.math.MaxEvaluationsExceededException
-
Constructs an exception with a default detail message.
- MaxEvaluationsExceededException(int, String, Object...) - Constructor for exception org.apache.commons.math.MaxEvaluationsExceededException
-
- MaxEvaluationsExceededException(int, Localizable, Object...) - Constructor for exception org.apache.commons.math.MaxEvaluationsExceededException
-
Constructs an exception with specified formatted detail message.
- maxGenerations - Variable in class org.apache.commons.math.genetics.FixedGenerationCount
-
Maximum number of generations (stopping criteria)
- maxGrowth - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
Maximal growth factor for stepsize control.
- maxGrowth - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Maximal growth factor for stepsize control.
- maximalIterationCount - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Maximum number of iterations.
- maxImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Maximum statistic implementation - can be reset by setter.
- maxImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Maximum statistic implementation - can be reset by setter.
- maxImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Maximum statistic implementation - can be reset by setter.
- maxIter - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Maximum number of iterations accepted in the implicit QL transformation
- maxIter - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
maximal number of iterations for which checks are performed.
- maxIterationCount - Variable in class org.apache.commons.math.ode.events.EventState
-
Upper limit in the iteration count for event localization.
- maxIterations - Variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Maximum number of iterations for cumulative probability.
- maxIterations - Variable in exception org.apache.commons.math.MaxIterationsExceededException
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Maximal number of iterations allowed.
- maxIterations - Variable in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Maximum number of iterations.
- MaxIterationsExceededException - Exception in org.apache.commons.math
-
Error thrown when a numerical computation exceeds its allowed
number of iterations.
- MaxIterationsExceededException(int) - Constructor for exception org.apache.commons.math.MaxIterationsExceededException
-
Constructs an exception with a default detail message.
- MaxIterationsExceededException(int, String, Object...) - Constructor for exception org.apache.commons.math.MaxIterationsExceededException
-
- MaxIterationsExceededException(int, Localizable, Object...) - Constructor for exception org.apache.commons.math.MaxIterationsExceededException
-
Constructs an exception with specified formatted detail message.
- maxOrder - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
maximal order.
- maxStep - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Maximal step.
- mdfft(Object, boolean) - Method in class org.apache.commons.math.transform.FastFourierTransformer
-
Performs a multi-dimensional Fourier transform on a given array.
- mdfft(FastFourierTransformer.MultiDimensionalComplexMatrix, boolean, int, int[]) - Method in class org.apache.commons.math.transform.FastFourierTransformer
-
Performs one dimension of a multi-dimensional Fourier transform.
- mean - Variable in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
The mean of this distribution.
- mean - Variable in class org.apache.commons.math.distribution.NormalDistributionImpl
-
The mean of this distribution.
- mean - Variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Holds the Poisson mean for the distribution.
- mean - Variable in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Mean vector.
- mean - Variable in class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
-
Mean vector.
- Mean - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes the arithmetic mean of a set of values.
- Mean() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Mean
-
Constructs a Mean.
- Mean(FirstMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Mean
-
Constructs a Mean with an External Moment.
- Mean(Mean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Mean
-
Copy constructor, creates a new Mean identical
to the original
- mean - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
The sample mean
- mean - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
mean of values that have been added
- MEAN - Static variable in class org.apache.commons.math.stat.StatUtils
-
mean
- mean(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the arithmetic mean of the entries in the input array, or
Double.NaN if the array is empty.
- mean(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the arithmetic mean of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- meanDifference(double[], double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the mean of the (signed) differences between corresponding elements of the
input arrays -- i.e., sum(sample1[i] - sample2[i]) / sample1.length.
- meanImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Mean statistic implementation - can be reset by setter.
- meanImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Mean statistic implementation - can be reset by setter.
- meanImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Mean statistic implementation - can be reset by setter.
- means - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
-
Means for each component.
- measuredValue - Variable in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Value of the measurements.
- measurements - Variable in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Array of measurements.
- measurements - Variable in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Measurements.
- median - Variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
The median of this distribution.
- Median - Class in org.apache.commons.math.stat.descriptive.rank
-
Returns the median of the available values.
- Median() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Median
-
Default constructor.
- Median(Median) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Median
-
Copy constructor, creates a new Median identical
to the original
- medianOf3(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Select a pivot index as the median of three
- MersenneTwister - Class in org.apache.commons.math.random
-
This class implements a powerful pseudo-random number generator
developed by Makoto Matsumoto and Takuji Nishimura during
1996-1997.
- MersenneTwister() - Constructor for class org.apache.commons.math.random.MersenneTwister
-
Creates a new random number generator.
- MersenneTwister(int) - Constructor for class org.apache.commons.math.random.MersenneTwister
-
Creates a new random number generator using a single int seed.
- MersenneTwister(int[]) - Constructor for class org.apache.commons.math.random.MersenneTwister
-
Creates a new random number generator using an int array seed.
- MersenneTwister(long) - Constructor for class org.apache.commons.math.random.MersenneTwister
-
Creates a new random number generator using a single long seed.
- MessageFactory - Class in org.apache.commons.math.exception.util
-
Class for constructing localized messages.
- MessageFactory() - Constructor for class org.apache.commons.math.exception.util.MessageFactory
-
Class contains only static methods.
- METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
-
Integrator method name.
- METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
-
Integrator method name.
- METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Integrator method name.
- METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Integrator method name.
- METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Integrator method name.
- METHOD_NAME - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
-
Integrator method name.
- microsphere - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
-
Internal accounting data for the interpolation algorithm.
- microsphereElements - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
-
Number of surface elements of the microsphere.
- MicrosphereInterpolatingFunction - Class in org.apache.commons.math.analysis.interpolation
-
- MicrosphereInterpolatingFunction(double[][], double[], int, int, UnitSphereRandomVectorGenerator) - Constructor for class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
-
- MicrosphereInterpolatingFunction.MicrosphereSurfaceElement - Class in org.apache.commons.math.analysis.interpolation
-
Class for storing the accounting data needed to perform the
microsphere projection.
- MicrosphereInterpolatingFunction.MicrosphereSurfaceElement(double[]) - Constructor for class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
-
- MicrosphereInterpolator - Class in org.apache.commons.math.analysis.interpolation
-
Interpolator that implements the algorithm described in
William Dudziak's
MS thesis.
- MicrosphereInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
-
Create a microsphere interpolator with default settings.
- MicrosphereInterpolator(int, int) - Constructor for class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
-
Create a microsphere interpolator.
- mid - Variable in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Point inside the bracket.
- midpoint(double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
-
Compute the midpoint of two values.
- MidpointIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements a second order Runge-Kutta integrator for
Ordinary Differential Equations.
- MidpointIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
-
Simple constructor.
- MidpointStepInterpolator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements a step interpolator for second order
Runge-Kutta integrator.
- MidpointStepInterpolator() - Constructor for class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
-
Simple constructor.
- MidpointStepInterpolator(MidpointStepInterpolator) - Constructor for class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
-
Copy constructor.
- min - Variable in exception org.apache.commons.math.exception.NumberIsTooSmallException
-
Higher bound.
- min - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Min loaded value
- Min - Class in org.apache.commons.math.stat.descriptive.rank
-
Returns the minimum of the available values.
- Min() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Min
-
Create a Min instance
- Min(Min) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Min
-
Copy constructor, creates a new Min identical
to the original
- min - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
The minimum value
- min - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
min of values that have been added
- MIN - Static variable in class org.apache.commons.math.stat.StatUtils
-
min
- min(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the minimum of the entries in the input array, or
Double.NaN if the array is empty.
- min(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the minimum of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- min(int, int) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the minimum of two values
- min(long, long) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the minimum of two values
- min(float, float) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the minimum of two values
- min(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the minimum of two values
- MIN_EXP - Static variable in class org.apache.commons.math.dfp.Dfp
-
The minimum exponent before underflow is signaled.
- MIN_SELECT_SIZE - Static variable in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Minimum size under which we use a simple insertion sort rather than Hoare's select.
- minimalIterationCount - Variable in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
minimum number of iterations
- minImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Minimum statistic implementation - can be reset by setter.
- minImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Minimum statistic implementation - can be reset by setter.
- minImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Minimum statistic implementation - can be reset by setter.
- minReduction - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
Minimal reduction factor for stepsize control.
- minReduction - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Minimal reduction factor for stepsize control.
- minStep - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Minimal step.
- MINUS_I - Static variable in class org.apache.commons.math.geometry.Vector3D
-
Opposite of the first canonical vector (coordinates: -1, 0, 0).
- MINUS_J - Static variable in class org.apache.commons.math.geometry.Vector3D
-
Opposite of the second canonical vector (coordinates: 0, -1, 0).
- MINUS_K - Static variable in class org.apache.commons.math.geometry.Vector3D
-
Opposite of the third canonical vector (coordinates: 0, 0, -1).
- MINUS_ONE - Static variable in class org.apache.commons.math.fraction.BigFraction
-
A fraction representing "-1 / 1".
- MINUS_ONE - Static variable in class org.apache.commons.math.fraction.Fraction
-
A fraction representing "-1 / 1".
- missingEntries - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Return value for missing entries.
- missingEntries - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Return value for missing entries.
- mode - Variable in class org.apache.commons.math.random.ValueServer
-
mode determines how values are generated.
- moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Fourth Moment on which this statistic is based
- moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Mean
-
First moment on which this statistic is based.
- moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Third moment on which this statistic is based
- moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Variance
-
SecondMoment is used in incremental calculation of Variance
- mt - Variable in class org.apache.commons.math.random.MersenneTwister
-
Bytes pool.
- mti - Variable in class org.apache.commons.math.random.MersenneTwister
-
Current index in the bytes pool.
- mu - Variable in class org.apache.commons.math.random.ValueServer
-
Mean for use with non-data-driven modes.
- mudif - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
interpolation order control parameter.
- mulAndCheck(int, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Multiply two integers, checking for overflow.
- mulAndCheck(long, long) - Static method in class org.apache.commons.math.util.MathUtils
-
Multiply two long integers, checking for overflow.
- MullerSolver - Class in org.apache.commons.math.analysis.solvers
-
Implements the
Muller's Method for root finding of real univariate functions.
- MullerSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.MullerSolver
-
- MullerSolver() - Constructor for class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- multiDimensionalComplexArray - Variable in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
-
Storage array.
- MultidimensionalCounter - Class in org.apache.commons.math.util
-
Converter between unidimensional storage structure and multidimensional
conceptual structure.
- MultidimensionalCounter(int...) - Constructor for class org.apache.commons.math.util.MultidimensionalCounter
-
Create a counter.
- MultidimensionalCounter.Iterator - Class in org.apache.commons.math.util
-
Perform iteration over the multidimensional counter.
- MultidimensionalCounter.Iterator() - Constructor for class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Create an iterator
- MultiDirectional - Class in org.apache.commons.math.optimization.direct
-
This class implements the multi-directional direct search method.
- MultiDirectional() - Constructor for class org.apache.commons.math.optimization.direct.MultiDirectional
-
Build a multi-directional optimizer with default coefficients.
- MultiDirectional(double, double) - Constructor for class org.apache.commons.math.optimization.direct.MultiDirectional
-
Build a multi-directional optimizer with specified coefficients.
- MultipleLinearRegression - Interface in org.apache.commons.math.stat.regression
-
The multiple linear regression can be represented in matrix-notation.
- MULTIPLICATIVE_MODE - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
-
multiplicative expansion mode
- MULTIPLY - Static variable in class org.apache.commons.math.analysis.BinaryFunction
-
Deprecated.
- multiply(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function multiplying the instance and another function.
- multiply(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function scaling the instance by a constant factor.
- multiply(PolynomialFunction) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Multiply the instance by a polynomial.
- multiply(Complex) - Method in class org.apache.commons.math.complex.Complex
-
Return the product of this complex number and the given complex number.
- multiply(double) - Method in class org.apache.commons.math.complex.Complex
-
Return the product of this complex number and the given scalar number.
- multiply(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Multiply this by x.
- multiply(int) - Method in class org.apache.commons.math.dfp.Dfp
-
Multiply this by a single digit 0<=x<radix.
- multiply(T) - Method in interface org.apache.commons.math.FieldElement
-
Compute this × a.
- multiply(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
-
Multiplies the value of this fraction by the passed
BigInteger, returning the result in reduced form.
- multiply(int) - Method in class org.apache.commons.math.fraction.BigFraction
-
Multiply the value of this fraction by the passed int, returning
the result in reduced form.
- multiply(long) - Method in class org.apache.commons.math.fraction.BigFraction
-
Multiply the value of this fraction by the passed long,
returning the result in reduced form.
- multiply(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
-
Multiplies the value of this fraction by another, returning the result in
reduced form.
- multiply(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
-
Multiplies the value of this fraction by another, returning the
result in reduced form.
- multiply(int) - Method in class org.apache.commons.math.fraction.Fraction
-
Multiply the fraction by an integer.
- multiply(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the result of postmultiplying this by m.
- multiply(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the result of postmultiplying this by m.
- multiply(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns the result of postmultiplying this by m.
- multiply(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns the result of postmultiplying this by m.
- multiply(RealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns the result of postmultiplying this by m.
- multiply(Array2DRowRealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns the result of postmultiplying this by m.
- multiply(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the result of postmultiplying this by m.
- multiply(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the result of postmultiplying this by m.
- multiply(BigMatrixImpl) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the result of postmultiplying this by m.
- multiply(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the result of postmultiplying this by m.
- multiply(BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the result of postmultiplying this by m.
- multiply(RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the result of postmultiplying this by m.
- multiply(BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the result of postmultiplying this by m.
- multiply(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the result of postmultiplying this by m.
- multiply(RealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns the result of postmultiplying this by m.
- multiply(OpenMapRealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns the result of postmultiplying this by m.
- multiply(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the result of postmultiplying this by m.
- multiply(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns the result of postmultiplying this by m.
- multiply(RealMatrixImpl) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns the result of postmultiplying this by m.
- multiply(BigReal) - Method in class org.apache.commons.math.util.BigReal
-
Compute this × a.
- MULTIPLY_TRAP - Static variable in class org.apache.commons.math.dfp.Dfp
-
Name for traps triggered by multiplication.
- multiplyEntry(int, int, T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, T) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Change an entry in the specified row and column.
- multiplyEntry(int, int, double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Change an entry in the specified row and column.
- multiplyEntry(int, int, T) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Change an entry in the specified row and column.
- MultiStartDifferentiableMultivariateRealOptimizer - Class in org.apache.commons.math.optimization
-
- MultiStartDifferentiableMultivariateRealOptimizer(DifferentiableMultivariateRealOptimizer, int, RandomVectorGenerator) - Constructor for class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Create a multi-start optimizer from a single-start optimizer
- MultiStartDifferentiableMultivariateVectorialOptimizer - Class in org.apache.commons.math.optimization
-
- MultiStartDifferentiableMultivariateVectorialOptimizer(DifferentiableMultivariateVectorialOptimizer, int, RandomVectorGenerator) - Constructor for class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Create a multi-start optimizer from a single-start optimizer
- MultiStartMultivariateRealOptimizer - Class in org.apache.commons.math.optimization
-
- MultiStartMultivariateRealOptimizer(MultivariateRealOptimizer, int, RandomVectorGenerator) - Constructor for class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Create a multi-start optimizer from a single-start optimizer
- MultiStartUnivariateRealOptimizer - Class in org.apache.commons.math.optimization
-
Special implementation of the
UnivariateRealOptimizer interface adding
multi-start features to an existing optimizer.
- MultiStartUnivariateRealOptimizer(UnivariateRealOptimizer, int, RandomGenerator) - Constructor for class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Create a multi-start optimizer from a single-start optimizer
- MultistepIntegrator - Class in org.apache.commons.math.ode
-
This class is the base class for multistep integrators for Ordinary
Differential Equations.
- MultistepIntegrator(String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.MultistepIntegrator
-
Build a multistep integrator with the given stepsize bounds.
- MultistepIntegrator(String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.MultistepIntegrator
-
Build a multistep integrator with the given stepsize bounds.
- MultistepIntegrator.CountingDifferentialEquations - Class in org.apache.commons.math.ode
-
Wrapper for differential equations, ensuring start evaluations are counted.
- MultistepIntegrator.CountingDifferentialEquations(int) - Constructor for class org.apache.commons.math.ode.MultistepIntegrator.CountingDifferentialEquations
-
Simple constructor.
- MultistepIntegrator.InitializationCompletedMarkerException - Exception in org.apache.commons.math.ode
-
Marker exception used ONLY to stop the starter integrator after first step.
- MultistepIntegrator.InitializationCompletedMarkerException() - Constructor for exception org.apache.commons.math.ode.MultistepIntegrator.InitializationCompletedMarkerException
-
Simple constructor.
- MultistepIntegrator.NordsieckInitializer - Class in org.apache.commons.math.ode
-
Specialized step handler storing the first step.
- MultistepIntegrator.NordsieckInitializer(int) - Constructor for class org.apache.commons.math.ode.MultistepIntegrator.NordsieckInitializer
-
Simple constructor.
- MultistepIntegrator.NordsieckTransformer - Interface in org.apache.commons.math.ode
-
Transformer used to convert the first step to Nordsieck representation.
- MultivariateMatrixFunction - Interface in org.apache.commons.math.analysis
-
An interface representing a multivariate matrix function.
- MultivariateRealFunction - Interface in org.apache.commons.math.analysis
-
An interface representing a multivariate real function.
- MultivariateRealInterpolator - Interface in org.apache.commons.math.analysis.interpolation
-
Interface representing a univariate real interpolating function.
- MultivariateRealOptimizer - Interface in org.apache.commons.math.optimization
-
- MultivariateSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
Computes summary statistics for a stream of n-tuples added using the
addValue method.
- MultivariateSummaryStatistics(int, boolean) - Constructor for class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Construct a MultivariateSummaryStatistics instance
- MultivariateVectorialFunction - Interface in org.apache.commons.math.analysis
-
An interface representing a multivariate vectorial function.
- mutate(Chromosome) - Method in class org.apache.commons.math.genetics.BinaryMutation
-
Mutate the given chromosome.
- mutate(Chromosome) - Method in interface org.apache.commons.math.genetics.MutationPolicy
-
Mutate the given chromosome.
- mutate(Chromosome) - Method in class org.apache.commons.math.genetics.RandomKeyMutation
-
Mutate the given chromosome.
- mutationPolicy - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
-
the mutation policy used by the algorithm.
- MutationPolicy - Interface in org.apache.commons.math.genetics
-
Algorithm used to mutate a chrommosome.
- mutationRate - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
-
the rate of mutation for the algorithm.
- N - Static variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineFunction
-
Number of points.
- N - Static variable in class org.apache.commons.math.analysis.interpolation.TricubicSplineFunction
-
Number of points.
- n - Variable in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
-
Number of spline segments = number of polynomials
= number of partition points - 1
- n - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Number of columns of the initial matrix.
- n - Variable in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepHandlerWrapper
-
Deprecated.
Dimension of the original ODE.
- n - Variable in class org.apache.commons.math.ode.MultistepIntegrator.NordsieckInitializer
-
Problem dimension.
- N - Static variable in class org.apache.commons.math.random.MersenneTwister
-
Size of the bytes pool.
- n - Variable in class org.apache.commons.math.stat.correlation.Covariance
-
Number of observations (length of covariate vectors)
- n - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Count of values that have been added
- n - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Number of vectors in the sample.
- n - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Count of values that have been added
- n - Variable in class org.apache.commons.math.stat.descriptive.rank.Max
-
Number of values that have been added
- n - Variable in class org.apache.commons.math.stat.descriptive.rank.Min
-
Number of values that have been added
- n - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
The number of observations in the sample
- n - Variable in class org.apache.commons.math.stat.descriptive.summary.Product
-
The number of values that have been added
- n - Variable in class org.apache.commons.math.stat.descriptive.summary.Sum
-
- n - Variable in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Number of values that have been added
- n - Variable in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
- n - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
count of values that have been added
- n - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
-
number of observations
- name - Variable in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Name of the parameter
- name - Variable in class org.apache.commons.math.geometry.RotationOrder
-
Name of the rotations order.
- name - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Name of the method.
- NaN - Static variable in class org.apache.commons.math.complex.Complex
-
A complex number representing "NaN + NaNi"
- NaN - Static variable in class org.apache.commons.math.geometry.Vector3D
-
A vector with all coordinates set to NaN.
- NAN_GAP - Static variable in class org.apache.commons.math.util.MathUtils
-
Gap between NaN and regular numbers.
- NAN_STRING - Static variable in class org.apache.commons.math.dfp.Dfp
-
String for NaN representation.
- nans - Variable in class org.apache.commons.math.dfp.Dfp
-
Indicator for non-finite / non-number values.
- NaNStrategy - Enum in org.apache.commons.math.stat.ranking
-
Strategies for handling NaN values in rank transformations.
- NaNStrategy() - Constructor for enum org.apache.commons.math.stat.ranking.NaNStrategy
-
- nanStrategy - Variable in class org.apache.commons.math.stat.ranking.NaturalRanking
-
NaN strategy - defaults to NaNs maximal
- NaturalRanking - Class in org.apache.commons.math.stat.ranking
-
Ranking based on the natural ordering on doubles.
- NaturalRanking() - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
-
Create a NaturalRanking with default strategies for handling ties and NaNs.
- NaturalRanking(TiesStrategy) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
-
Create a NaturalRanking with the given TiesStrategy.
- NaturalRanking(NaNStrategy) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
-
Create a NaturalRanking with the given NaNStrategy.
- NaturalRanking(NaNStrategy, TiesStrategy) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
-
Create a NaturalRanking with the given NaNStrategy and TiesStrategy.
- NaturalRanking(RandomGenerator) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
-
Create a NaturalRanking with TiesStrategy.RANDOM and the given
RandomGenerator as the source of random data.
- NaturalRanking(NaNStrategy, RandomGenerator) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking
-
Create a NaturalRanking with the given NaNStrategy, TiesStrategy.RANDOM
and the given source of random data.
- NaturalRanking.IntDoublePair - Class in org.apache.commons.math.stat.ranking
-
Represents the position of a double value in an ordering.
- NaturalRanking.IntDoublePair(double, int) - Constructor for class org.apache.commons.math.stat.ranking.NaturalRanking.IntDoublePair
-
Construct an IntDoublePair with the given value and position.
- NB - Static variable in class org.apache.commons.math.util.MathUtils
-
-1.0 cast as a byte.
- nDev - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Deviation of most recently added value from previous first moment,
normalized by previous sample size.
- nDevSq - Variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Square of deviation of most recently added value from previous first
moment, normalized by previous sample size.
- NEG_INFINITY_STRING - Static variable in class org.apache.commons.math.dfp.Dfp
-
String for negative infinity representation.
- NEGATE - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- negate() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Negate the instance.
- negate() - Method in class org.apache.commons.math.complex.Complex
-
Return the additive inverse of this complex number.
- negate() - Method in class org.apache.commons.math.dfp.Dfp
-
Returns a number that is this number with the sign bit reversed.
- negate() - Method in class org.apache.commons.math.fraction.BigFraction
-
Return the additive inverse of this fraction, returning the result in
reduced form.
- negate() - Method in class org.apache.commons.math.fraction.Fraction
-
Return the additive inverse of this fraction.
- negate() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the opposite of the instance.
- NEGATIVE_INFINITY - Static variable in class org.apache.commons.math.geometry.Vector3D
-
A vector with all coordinates set to negative infinity.
- NEGATIVE_VAR_COLUMN_LABEL - Static variable in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Column label for negative vars.
- NelderMead - Class in org.apache.commons.math.optimization.direct
-
This class implements the Nelder-Mead direct search method.
- NelderMead() - Constructor for class org.apache.commons.math.optimization.direct.NelderMead
-
Build a Nelder-Mead optimizer with default coefficients.
- NelderMead(double, double, double, double) - Constructor for class org.apache.commons.math.optimization.direct.NelderMead
-
Build a Nelder-Mead optimizer with specified coefficients.
- NevilleInterpolator - Class in org.apache.commons.math.analysis.interpolation
-
- NevilleInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.NevilleInterpolator
-
- NEW_INSTANCE_TRAP - Static variable in class org.apache.commons.math.dfp.Dfp
-
Name for traps triggered by newInstance.
- newBisectionSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
-
- newBisectionSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
-
- newBrentSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
-
- newBrentSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
-
- newCovarianceData(double[][]) - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Add the covariance data.
- newDefaultSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
-
- newDefaultSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
-
- newDfp() - Method in class org.apache.commons.math.dfp.DfpField
-
Makes a
Dfp with a value of 0.
- newDfp(byte) - Method in class org.apache.commons.math.dfp.DfpField
-
Create an instance from a byte value.
- newDfp(int) - Method in class org.apache.commons.math.dfp.DfpField
-
Create an instance from an int value.
- newDfp(long) - Method in class org.apache.commons.math.dfp.DfpField
-
Create an instance from a long value.
- newDfp(double) - Method in class org.apache.commons.math.dfp.DfpField
-
Create an instance from a double value.
- newDfp(Dfp) - Method in class org.apache.commons.math.dfp.DfpField
-
Copy constructor.
- newDfp(String) - Method in class org.apache.commons.math.dfp.DfpField
-
Create a
Dfp given a String representation.
- newDfp(byte, byte) - Method in class org.apache.commons.math.dfp.DfpField
-
Creates a
Dfp with a non-finite value.
- newFixedLengthChromosome(List<T>) - Method in class org.apache.commons.math.genetics.AbstractListChromosome
-
Creates a new instance of the same class as this is, with a
given arrayRepresentation.
- newInstance() - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
-
Create a new factory.
- newInstance() - Method in class org.apache.commons.math.dfp.Dfp
-
Create an instance with a value of 0.
- newInstance(byte) - Method in class org.apache.commons.math.dfp.Dfp
-
Create an instance from a byte value.
- newInstance(int) - Method in class org.apache.commons.math.dfp.Dfp
-
Create an instance from an int value.
- newInstance(long) - Method in class org.apache.commons.math.dfp.Dfp
-
Create an instance from a long value.
- newInstance(double) - Method in class org.apache.commons.math.dfp.Dfp
-
Create an instance from a double value.
- newInstance(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Create an instance by copying an existing one.
- newInstance(String) - Method in class org.apache.commons.math.dfp.Dfp
-
Create an instance from a String representation.
- newInstance(byte, byte) - Method in class org.apache.commons.math.dfp.Dfp
-
Creates an instance with a non-finite value.
- newInstance() - Method in class org.apache.commons.math.dfp.DfpDec
-
Create an instance with a value of 0.
- newInstance(byte) - Method in class org.apache.commons.math.dfp.DfpDec
-
Create an instance from a byte value.
- newInstance(int) - Method in class org.apache.commons.math.dfp.DfpDec
-
Create an instance from an int value.
- newInstance(long) - Method in class org.apache.commons.math.dfp.DfpDec
-
Create an instance from a long value.
- newInstance(double) - Method in class org.apache.commons.math.dfp.DfpDec
-
Create an instance from a double value.
- newInstance(Dfp) - Method in class org.apache.commons.math.dfp.DfpDec
-
Create an instance by copying an existing one.
- newInstance(String) - Method in class org.apache.commons.math.dfp.DfpDec
-
Create an instance from a String representation.
- newInstance(byte, byte) - Method in class org.apache.commons.math.dfp.DfpDec
-
Creates an instance with a non-finite value.
- newNewtonSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
-
- newNewtonSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
-
- newPointAndDirection(double[], double[], double) - Method in class org.apache.commons.math.optimization.direct.PowellOptimizer
-
Compute a new point (in the original space) and a new direction
vector, resulting from the line search.
- newSampleData(double[], int, int) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Loads model x and y sample data from a flat input array, overriding any previous sample.
- newSampleData(double[], double[][], double[][]) - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Replace sample data, overriding any previous sample.
- newSampleData(double[], double[][]) - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Loads model x and y sample data, overriding any previous sample.
- newSampleData(double[], int, int) - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Loads model x and y sample data from a flat input array, overriding any previous sample.
- newSecantSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactory
-
- newSecantSolver() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverFactoryImpl
-
- NewtonSolver - Class in org.apache.commons.math.analysis.solvers
-
- NewtonSolver(DifferentiableUnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.NewtonSolver
-
- NewtonSolver() - Constructor for class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- newXSampleData(double[][]) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Loads new x sample data, overriding any previous data.
- newXSampleData(double[][]) - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Loads new x sample data, overriding any previous data.
- newYSampleData(double[]) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Loads new y sample data, overriding any previous data.
- next - Variable in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
-
- next() - Method in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
- next() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapSparseIterator
- next(int) - Method in class org.apache.commons.math.random.AbstractWell
-
Generate next pseudorandom number.
- next(int) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Generate next pseudorandom number.
- next(int) - Method in class org.apache.commons.math.random.MersenneTwister
-
Generate next pseudorandom number.
- next(int) - Method in class org.apache.commons.math.random.Well1024a
-
Generate next pseudorandom number.
- next(int) - Method in class org.apache.commons.math.random.Well19937a
-
Generate next pseudorandom number.
- next(int) - Method in class org.apache.commons.math.random.Well19937c
-
Generate next pseudorandom number.
- next(int) - Method in class org.apache.commons.math.random.Well44497a
-
Generate next pseudorandom number.
- next(int) - Method in class org.apache.commons.math.random.Well44497b
-
Generate next pseudorandom number.
- next(int) - Method in class org.apache.commons.math.random.Well512a
-
Generate next pseudorandom number.
- next() - Method in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
- next - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
-
Index of next element.
- next - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
-
Index of next element.
- NEXT_AFTER_TRAP - Static variable in class org.apache.commons.math.dfp.Dfp
-
Name for traps triggered by nextAfter.
- nextAction - Variable in class org.apache.commons.math.ode.events.EventState
-
Next action indicator.
- nextAfter(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Returns the next number greater than this one in the direction of x.
- nextAfter(Dfp) - Method in class org.apache.commons.math.dfp.DfpDec
-
Returns the next number greater than this one in the direction of x.
- nextAfter(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Get the next machine representable number after a number, moving
in the direction of another number.
- nextAfter(float, double) - Static method in class org.apache.commons.math.util.FastMath
-
Get the next machine representable number after a number, moving
in the direction of another number.
- nextAfter(double, double) - Static method in class org.apache.commons.math.util.MathUtils
-
- nextBeta(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextBinomial(int, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextBoolean() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Returns the next pseudorandom, uniformly distributed
boolean value from this random number generator's
sequence.
- nextBoolean() - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Returns the next pseudorandom, uniformly distributed
boolean value from this random number generator's
sequence.
- nextBoolean() - Method in class org.apache.commons.math.random.RandomAdaptor
-
Returns the next pseudorandom, uniformly distributed
boolean value from this random number generator's
sequence.
- nextBoolean() - Method in interface org.apache.commons.math.random.RandomGenerator
-
Returns the next pseudorandom, uniformly distributed
boolean value from this random number generator's
sequence.
- nextBytes(byte[]) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Generates random bytes and places them into a user-supplied
byte array.
- nextBytes(byte[]) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Generates random bytes and places them into a user-supplied
byte array.
- nextBytes(byte[]) - Method in class org.apache.commons.math.random.RandomAdaptor
-
Generates random bytes and places them into a user-supplied
byte array.
- nextBytes(byte[]) - Method in interface org.apache.commons.math.random.RandomGenerator
-
Generates random bytes and places them into a user-supplied
byte array.
- nextCauchy(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextChiSquare(double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextDouble() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Returns the next pseudorandom, uniformly distributed
double value between 0.0 and
1.0 from this random number generator's sequence.
- nextDouble() - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Returns the next pseudorandom, uniformly distributed
double value between 0.0 and
1.0 from this random number generator's sequence.
- nextDouble() - Method in class org.apache.commons.math.random.RandomAdaptor
-
Returns the next pseudorandom, uniformly distributed
double value between 0.0 and
1.0 from this random number generator's sequence.
- nextDouble() - Method in interface org.apache.commons.math.random.RandomGenerator
-
Returns the next pseudorandom, uniformly distributed
double value between 0.0 and
1.0 from this random number generator's sequence.
- nextExponential(double) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a random value from the exponential distribution
with expected value = mean.
- nextExponential(double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Returns a random value from an Exponential distribution with the given
mean.
- nextF(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextFloat() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Returns the next pseudorandom, uniformly distributed float
value between 0.0 and 1.0 from this random
number generator's sequence.
- nextFloat() - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Returns the next pseudorandom, uniformly distributed float
value between 0.0 and 1.0 from this random
number generator's sequence.
- nextFloat() - Method in class org.apache.commons.math.random.RandomAdaptor
-
Returns the next pseudorandom, uniformly distributed float
value between 0.0 and 1.0 from this random
number generator's sequence.
- nextFloat() - Method in interface org.apache.commons.math.random.RandomGenerator
-
Returns the next pseudorandom, uniformly distributed float
value between 0.0 and 1.0 from this random
number generator's sequence.
- nextGamma(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextGaussian() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Returns the next pseudorandom, Gaussian ("normally") distributed
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
- nextGaussian - Variable in class org.apache.commons.math.random.BitsStreamGenerator
-
Next gaussian.
- nextGaussian() - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Returns the next pseudorandom, Gaussian ("normally") distributed
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
- nextGaussian() - Method in class org.apache.commons.math.random.RandomAdaptor
-
Returns the next pseudorandom, Gaussian ("normally") distributed
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
- nextGaussian(double, double) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a random value from the
Normal (or Gaussian) distribution with the given mean
and standard deviation.
- nextGaussian(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generate a random value from a Normal (a.k.a.
- nextGaussian() - Method in interface org.apache.commons.math.random.RandomGenerator
-
Returns the next pseudorandom, Gaussian ("normally") distributed
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
- nextGeneration() - Method in class org.apache.commons.math.genetics.ElitisticListPopulation
-
Start the population for the next generation.
- nextGeneration(Population) - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Evolve the given population into the next generation.
- nextGeneration() - Method in interface org.apache.commons.math.genetics.Population
-
Start the population for the next generation.
- nextHexString(int) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a random string of hex characters of length
len.
- nextHexString(int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generates a random string of hex characters of length
len.
- nextHypergeometric(int, int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextIndex(int, int) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolator
-
Compute the next index of an array, clipping if necessary.
- nextIndex(int, int) - Method in class org.apache.commons.math.analysis.interpolation.SmoothingBicubicSplineInterpolator
-
Deprecated.
Compute the next index of an array, clipping if necessary.
- nextIndex(int, int) - Method in class org.apache.commons.math.analysis.interpolation.TricubicSplineInterpolator
-
Compute the next index of an array, clipping if necessary.
- nextInt() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Returns the next pseudorandom, uniformly distributed int
value from this random number generator's sequence.
- nextInt(int) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Returns a pseudorandom, uniformly distributed int value
between 0 (inclusive) and the specified value (exclusive), drawn from
this random number generator's sequence.
- nextInt() - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Returns the next pseudorandom, uniformly distributed int
value from this random number generator's sequence.
- nextInt(int) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Returns a pseudorandom, uniformly distributed int value
between 0 (inclusive) and the specified value (exclusive), drawn from
this random number generator's sequence.
- nextInt() - Method in class org.apache.commons.math.random.RandomAdaptor
-
Returns the next pseudorandom, uniformly distributed int
value from this random number generator's sequence.
- nextInt(int) - Method in class org.apache.commons.math.random.RandomAdaptor
-
Returns a pseudorandom, uniformly distributed int value
between 0 (inclusive) and the specified value (exclusive), drawn from
this random number generator's sequence.
- nextInt(int, int) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a uniformly distributed random integer between
lower and upper (endpoints included).
- nextInt(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generate a random int value uniformly distributed between
lower and upper, inclusive.
- nextInt() - Method in interface org.apache.commons.math.random.RandomGenerator
-
Returns the next pseudorandom, uniformly distributed int
value from this random number generator's sequence.
- nextInt(int) - Method in interface org.apache.commons.math.random.RandomGenerator
-
Returns a pseudorandom, uniformly distributed int value
between 0 (inclusive) and the specified value (exclusive), drawn from
this random number generator's sequence.
- nextInversionDeviate(ContinuousDistribution) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextInversionDeviate(IntegerDistribution) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextLong() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Returns the next pseudorandom, uniformly distributed long
value from this random number generator's sequence.
- nextLong() - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Returns the next pseudorandom, uniformly distributed long
value from this random number generator's sequence.
- nextLong() - Method in class org.apache.commons.math.random.RandomAdaptor
-
Returns the next pseudorandom, uniformly distributed long
value from this random number generator's sequence.
- nextLong(long, long) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a uniformly distributed random long integer between
lower and upper (endpoints included).
- nextLong(long, long) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generate a random long value uniformly distributed between
lower and upper, inclusive.
- nextLong() - Method in interface org.apache.commons.math.random.RandomGenerator
-
Returns the next pseudorandom, uniformly distributed long
value from this random number generator's sequence.
- nextNonzero(double[], int) - Static method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
Returns the smallest index j such that j > i && (j==weights.length || weights[j] != 0)
- nextNormalizedDouble() - Method in class org.apache.commons.math.random.GaussianRandomGenerator
-
Generate a random scalar with null mean and unit standard deviation.
- nextNormalizedDouble() - Method in interface org.apache.commons.math.random.NormalizedRandomGenerator
-
Generate a random scalar with null mean and unit standard deviation.
- nextNormalizedDouble() - Method in class org.apache.commons.math.random.UniformRandomGenerator
-
Generate a random scalar with null mean and unit standard deviation.
- nextPascal(int, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextPermutation(int, int) - Method in interface org.apache.commons.math.random.RandomData
-
Generates an integer array of length k whose entries
are selected randomly, without repetition, from the integers
0 through n-1 (inclusive).
- nextPermutation(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generates an integer array of length k whose entries are
selected randomly, without repetition, from the integers
0 through n-1 (inclusive).
- nextPoisson(double) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a random value from the Poisson distribution with
the given mean.
- nextPoisson(double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generates a random value from the Poisson distribution with
the given mean.
- nextPowerOfTwo(int) - Static method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Find the smallest power of two greater than the input value
- nextPowerOfTwo(int) - Static method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Find the smallest power of two greater than the input value
- nextSample(Collection<?>, int) - Method in interface org.apache.commons.math.random.RandomData
-
Returns an array of k objects selected randomly
from the Collection c.
- nextSample(Collection<?>, int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Uses a 2-cycle permutation shuffle to generate a random permutation.
- nextSecureHexString(int) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a random string of hex characters from a secure random
sequence.
- nextSecureHexString(int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generates a random string of hex characters from a secure random
sequence.
- nextSecureInt(int, int) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a uniformly distributed random integer between
lower and upper (endpoints included)
from a secure random sequence.
- nextSecureInt(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generate a random int value uniformly distributed between
lower and upper, inclusive.
- nextSecureLong(long, long) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a random long integer between lower
and upper (endpoints included).
- nextSecureLong(long, long) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generate a random long value uniformly distributed between
lower and upper, inclusive.
- nextT(double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextUniform(double, double) - Method in interface org.apache.commons.math.random.RandomData
-
Generates a uniformly distributed random value from the open interval
(lower,upper) (i.e., endpoints excluded).
- nextUniform(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Generates a uniformly distributed random value from the open interval
(lower,upper) (i.e., endpoints excluded).
- nextUp(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute next number towards positive infinity.
- nextUp(float) - Static method in class org.apache.commons.math.util.FastMath
-
Compute next number towards positive infinity.
- nextVector() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Generate a correlated random vector.
- nextVector() - Method in interface org.apache.commons.math.random.RandomVectorGenerator
-
Generate a random vector.
- nextVector() - Method in class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
-
Generate an uncorrelated random vector.
- nextVector() - Method in class org.apache.commons.math.random.UnitSphereRandomVectorGenerator
-
Generate a random vector.
- nextWeibull(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nextZipf(int, double) - Method in class org.apache.commons.math.random.RandomDataImpl
-
- nObs - Variable in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
number of observations
- NoDataException - Exception in org.apache.commons.math.exception
-
Exception to be thrown when the required data is missing.
- NoDataException() - Constructor for exception org.apache.commons.math.exception.NoDataException
-
Construct the exception.
- NoDataException(Localizable) - Constructor for exception org.apache.commons.math.exception.NoDataException
-
Construct the exception with a specific context.
- NoFeasibleSolutionException - Exception in org.apache.commons.math.optimization.linear
-
This class represents exceptions thrown by optimizers when no solution
fulfills the constraints.
- NoFeasibleSolutionException() - Constructor for exception org.apache.commons.math.optimization.linear.NoFeasibleSolutionException
-
Simple constructor using a default message.
- noIntercept - Variable in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Whether or not the regression model includes an intercept.
- NonLinearConjugateGradientOptimizer - Class in org.apache.commons.math.optimization.general
-
Non-linear conjugate gradient optimizer.
- NonLinearConjugateGradientOptimizer(ConjugateGradientFormula) - Constructor for class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
Simple constructor with default settings.
- NonLinearConjugateGradientOptimizer.IdentityPreconditioner - Class in org.apache.commons.math.optimization.general
-
Default identity preconditioner.
- NonLinearConjugateGradientOptimizer.IdentityPreconditioner() - Constructor for class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer.IdentityPreconditioner
-
- NonLinearConjugateGradientOptimizer.LineSearchFunction - Class in org.apache.commons.math.optimization.general
-
Internal class for line search.
- NonLinearConjugateGradientOptimizer.LineSearchFunction(double[]) - Constructor for class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer.LineSearchFunction
-
Simple constructor.
- NonMonotonousSequenceException - Exception in org.apache.commons.math.exception
-
Exception to be thrown when the a sequence of values is not monotonously
increasing or decreasing.
- NonMonotonousSequenceException(Number, Number, int) - Constructor for exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
Construct the exception.
- NonMonotonousSequenceException(Number, Number, int, MathUtils.OrderDirection, boolean) - Constructor for exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
Construct the exception.
- nonNegative - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Whether to restrict the variables to non-negative values.
- nonSingular - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
-
Singularity indicator.
- NonSquareMatrixException - Exception in org.apache.commons.math.linear
-
Thrown when an operation defined only for square matrices is applied to non-square ones.
- NonSquareMatrixException(int, int) - Constructor for exception org.apache.commons.math.linear.NonSquareMatrixException
-
Construct an exception with the given message.
- nordsieck - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
Nordsieck matrix of the higher scaled derivatives.
- nordsieck - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Nordsieck vector.
- NordsieckStepInterpolator - Class in org.apache.commons.math.ode.sampling
-
This class implements an interpolator for integrators using Nordsieck representation.
- NordsieckStepInterpolator() - Constructor for class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Simple constructor.
- NordsieckStepInterpolator(NordsieckStepInterpolator) - Constructor for class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Copy constructor.
- normal - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
-
Normal vector characterizing a surface element.
- normal() - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
-
Return the normal vector.
- normal - Variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Distribution used to compute normal approximation.
- normalApproximateProbability(int) - Method in interface org.apache.commons.math.distribution.PoissonDistribution
-
Calculates the Poisson distribution function using a normal approximation.
- normalApproximateProbability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Calculates the Poisson distribution function using a normal
approximation.
- NormalDistribution - Interface in org.apache.commons.math.distribution
-
Normal (Gauss) Distribution.
- NormalDistributionImpl - Class in org.apache.commons.math.distribution
-
- NormalDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.NormalDistributionImpl
-
Create a normal distribution using the given mean and standard deviation.
- NormalDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.NormalDistributionImpl
-
Create a normal distribution using the given mean, standard deviation and
inverse cumulative distribution accuracy.
- NormalDistributionImpl() - Constructor for class org.apache.commons.math.distribution.NormalDistributionImpl
-
Creates normal distribution with the mean equal to zero and standard
deviation equal to one.
- normalize() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get a normalized vector aligned with the instance.
- normalize(LinearConstraint) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get a new equation equivalent to this one with a positive right hand side.
- normalize(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Normalize (standardize) the series, so in the end it is having a mean of 0 and a standard deviation of 1.
- normalizeAngle(double, double) - Static method in class org.apache.commons.math.util.MathUtils
-
Normalize an angle in a 2&pi wide interval around a center value.
- normalizeArray(double[], double) - Static method in class org.apache.commons.math.util.MathUtils
-
Normalizes an array to make it sum to a specified value.
- normalizeConstraints(Collection<LinearConstraint>) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Get new versions of the constraints which have positive right hand sides.
- normalized - Variable in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Storage for the normalized vector.
- NormalizedRandomGenerator - Interface in org.apache.commons.math.random
-
This interface represent a normalized random generator for
scalars.
- NotARotationMatrixException - Exception in org.apache.commons.math.geometry
-
This class represents exceptions thrown while building rotations
from matrices.
- NotARotationMatrixException(String, Object...) - Constructor for exception org.apache.commons.math.geometry.NotARotationMatrixException
-
- NotARotationMatrixException(Localizable, Object...) - Constructor for exception org.apache.commons.math.geometry.NotARotationMatrixException
-
Simple constructor.
- NotPositiveDefiniteMatrixException - Exception in org.apache.commons.math.linear
-
This class represents exceptions thrown when a matrix expected to
be positive definite is not.
- NotPositiveDefiniteMatrixException() - Constructor for exception org.apache.commons.math.linear.NotPositiveDefiniteMatrixException
-
Simple constructor.
- NotPositiveException - Exception in org.apache.commons.math.exception
-
Exception to be thrown when the argument is negative.
- NotPositiveException(Number) - Constructor for exception org.apache.commons.math.exception.NotPositiveException
-
Construct the exception.
- NotPositiveException(Localizable, Number) - Constructor for exception org.apache.commons.math.exception.NotPositiveException
-
Construct the exception with a specific context.
- NotStrictlyPositiveException - Exception in org.apache.commons.math.exception
-
Exception to be thrown when the argument is negative.
- NotStrictlyPositiveException(Number) - Constructor for exception org.apache.commons.math.exception.NotStrictlyPositiveException
-
Construct the exception.
- NotStrictlyPositiveException(Localizable, Number) - Constructor for exception org.apache.commons.math.exception.NotStrictlyPositiveException
-
Construct the exception with a specific context.
- NotSymmetricMatrixException - Exception in org.apache.commons.math.linear
-
This class represents exceptions thrown when a matrix expected to
be symmetric is not
- NotSymmetricMatrixException() - Constructor for exception org.apache.commons.math.linear.NotSymmetricMatrixException
-
Simple constructor.
- NS - Static variable in class org.apache.commons.math.util.MathUtils
-
-1.0 cast as a short.
- nSteps - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
Number of steps of the multistep method (excluding the one being computed).
- nthRoot(int) - Method in class org.apache.commons.math.complex.Complex
-
Computes the n-th roots of this complex number.
- NullArgumentException - Exception in org.apache.commons.math.exception
-
All conditions checks that fail due to a null argument must throw
this exception.
- NullArgumentException() - Constructor for exception org.apache.commons.math.exception.NullArgumentException
-
Default constructor.
- NullArgumentException(Localizable) - Constructor for exception org.apache.commons.math.exception.NullArgumentException
-
- numArtificialVariables - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Number of artificial variables.
- NumberIsTooLargeException - Exception in org.apache.commons.math.exception
-
Exception to be thrown when a number is too large.
- NumberIsTooLargeException(Number, Number, boolean) - Constructor for exception org.apache.commons.math.exception.NumberIsTooLargeException
-
Construct the exception.
- NumberIsTooLargeException(Localizable, Number, Number, boolean) - Constructor for exception org.apache.commons.math.exception.NumberIsTooLargeException
-
Construct the exception with a specific context.
- NumberIsTooSmallException - Exception in org.apache.commons.math.exception
-
Exception to be thrown when a number is too small.
- NumberIsTooSmallException(Number, Number, boolean) - Constructor for exception org.apache.commons.math.exception.NumberIsTooSmallException
-
Construct the exception.
- NumberIsTooSmallException(Localizable, Number, Number, boolean) - Constructor for exception org.apache.commons.math.exception.NumberIsTooSmallException
-
Construct the exception with a specific context.
- numberOfElements - Variable in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Number of elements.
- numberOfSuccesses - Variable in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
The number of successes in the population.
- numberOfSuccesses - Variable in class org.apache.commons.math.distribution.PascalDistributionImpl
-
The number of successes
- numberOfTrials - Variable in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
The number of trials.
- NumberTransformer - Interface in org.apache.commons.math.util
-
Subclasses implementing this interface can transform Objects to doubles.
- numDecisionVariables - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Number of decision variables.
- numElements - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
The number of addressable elements in the array.
- numerator - Variable in class org.apache.commons.math.fraction.BigFraction
-
The numerator.
- numerator - Variable in class org.apache.commons.math.fraction.Fraction
-
The numerator.
- numeratorDegreesOfFreedom - Variable in class org.apache.commons.math.distribution.FDistributionImpl
-
The numerator degrees of freedom
- numeratorFormat - Variable in class org.apache.commons.math.fraction.AbstractFormat
-
The format used for the numerator.
- numericalMean - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Cached numerical mean
- numericalMeanIsCalculated - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Whether or not the numerical mean has been calculated
- numericalVariance - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Cached numerical variance
- numericalVarianceIsCalculated - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Whether or not the numerical variance has been calculated
- numGenerations - Variable in class org.apache.commons.math.genetics.FixedGenerationCount
-
Number of generations that have passed
- numSlackVariables - Variable in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Number of slack variables.
- s - Variable in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
-
Intermediate result.
- S_LIMIT - Static variable in class org.apache.commons.math.special.Gamma
-
S limit.
- SaddlePointExpansion - Class in org.apache.commons.math.distribution
-
Utility class used by various distributions to accurately compute their
respective probability mass functions.
- SaddlePointExpansion() - Constructor for class org.apache.commons.math.distribution.SaddlePointExpansion
-
Default constructor.
- SAFE_MIN - Static variable in class org.apache.commons.math.util.MathUtils
-
Safe minimum, such that 1 / SAFE_MIN does not overflow.
- safeNorm(double[]) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the Cartesian norm (2-norm), handling both overflow and underflow.
- safety - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
Safety factor for stepsize control.
- safety - Variable in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Safety factor for stepsize control.
- sample() - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
-
Get the sample illuminating the element the most.
- sample() - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Generates a random value sampled from this distribution.
- sample(int) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Generates a random sample from the distribution.
- sample() - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Generates a random value sampled from this distribution.
- sample(int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Generates a random sample from the distribution.
- sample() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Generates a random value sampled from this distribution.
- sample() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Generates a random value sampled from this distribution.
- sample() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Generates a random value sampled from this distribution.
- sample(UnivariateRealFunction, double, double, int) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
-
Sample the given univariate real function on the given interval.
- samples - Variable in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction
-
Sample data.
- sampleSize - Variable in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
The sample size.
- sampleStats - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Sample statistics
- sanityChecks(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Perform some sanity checks on the integration parameters.
- sanityChecks(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Perform some sanity checks on the integration parameters.
- scalAbsoluteTolerance - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Allowed absolute scalar error.
- scalarAdd(T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(BigDecimal) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the result of adding d to each entry of this.
- scalarAdd(BigDecimal) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the result of adding d to each entry of this.
- scalarAdd(T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the result of adding d to each entry of this.
- scalarMultiply(double) - Method in class org.apache.commons.math.geometry.Vector3D
-
Multiply the instance by a scalar
- scalarMultiply(T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(BigDecimal) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the result multiplying each entry of this by d.
- scalarMultiply(BigDecimal) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the result of multiplying each entry of this by d
- scalarMultiply(T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the result multiplying each entry of this by d.
- scalb(double, int) - Static method in class org.apache.commons.math.util.FastMath
-
Multiply a double number by a power of 2.
- scalb(float, int) - Static method in class org.apache.commons.math.util.FastMath
-
Multiply a float number by a power of 2.
- scalb(double, int) - Static method in class org.apache.commons.math.util.MathUtils
-
- scale - Variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
The scale of this distribution.
- scale - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
The scale parameter.
- scale - Variable in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
BigDecimal scale
- scale - Variable in class org.apache.commons.math.optimization.LeastSquaresConverter
-
Optional scaling matrix (weight and correlations) for the residuals.
- scale - Variable in class org.apache.commons.math.util.BigReal
-
BigDecimal scale
- scaleArray(double[], double) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
-
Multiply every component in the given real array by the
given real number.
- scaleArray(Complex[], double) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
-
Multiply every component in the given complex array by the
given real number.
- scaled - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
First scaled derivative (h y').
- scaled - Variable in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
-
Current scaled first derivative.
- scaled - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
First scaled derivative.
- scalingH - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Step size used in the first scaled derivative and Nordsieck vector.
- scalRelativeTolerance - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Allowed relative scalar error.
- search(double[], double[]) - Method in class org.apache.commons.math.optimization.direct.PowellOptimizer.LineSearch
-
Find the minimum of the function f(p + alpha * d).
- search(UnivariateRealFunction, GoalType, double, double) - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Search new points that bracket a local optimum of the function.
- searchDirection - Variable in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer.LineSearchFunction
-
Search direction.
- searchForFitnessUpdate(Population) - Method in class org.apache.commons.math.genetics.Chromosome
-
Searches the population for a chromosome representing the same solution,
and if it finds one, updates the fitness to its value.
- searchIndex(double, double[]) - Method in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
-
- searchIndex(double, double[]) - Method in class org.apache.commons.math.analysis.interpolation.TricubicSplineInterpolatingFunction
-
- searchMax - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Higher end of search interval.
- searchMin - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Lower end of search interval.
- searchStart - Variable in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Initial guess .
- SecantSolver - Class in org.apache.commons.math.analysis.solvers
-
Implements a modified version of the
secant method
for approximating a zero of a real univariate function.
- SecantSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.SecantSolver
-
- SecantSolver() - Constructor for class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- second - Variable in class org.apache.commons.math.genetics.ChromosomePair
-
the second chromosome in the pair.
- secondary - Variable in class org.apache.commons.math.linear.BiDiagonalTransformer
-
Secondary diagonal.
- secondary - Variable in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Secondary diagonal of the tridiagonal matrix.
- secondary - Variable in class org.apache.commons.math.linear.TriDiagonalTransformer
-
Secondary diagonal.
- SecondMoment - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes a statistic related to the Second Central Moment.
- SecondMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Create a SecondMoment instance
- SecondMoment(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Copy constructor, creates a new SecondMoment identical
to the original
- secondMoment - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
SecondMoment is used to compute the mean and variance
- SecondOrderDifferentialEquations - Interface in org.apache.commons.math.ode
-
This interface represents a second order differential equations set.
- SecondOrderIntegrator - Interface in org.apache.commons.math.ode
-
This interface represents a second order integrator for
differential equations.
- secRand - Variable in class org.apache.commons.math.random.RandomDataImpl
-
underlying secure random number generator
- select(Population) - Method in interface org.apache.commons.math.genetics.SelectionPolicy
-
Select two chromosomes from the population.
- select(Population) - Method in class org.apache.commons.math.genetics.TournamentSelection
-
Select two chromosomes from the population.
- select(double[], int[], int) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Select the kth smallest element from work array
- selectionPolicy - Variable in class org.apache.commons.math.genetics.GeneticAlgorithm
-
the selection policy used by the algorithm.
- SelectionPolicy - Interface in org.apache.commons.math.genetics
-
Algorithm used to select a chromosome pair from a population.
- SemiVariance - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes the semivariance of a set of values with respect to a given cutoff value.
- SemiVariance() - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Constructs a SemiVariance with default (true) biasCorrected
property and default (Downside) varianceDirection property.
- SemiVariance(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Constructs a SemiVariance with the specified biasCorrected
property and default (Downside) varianceDirection property.
- SemiVariance(SemiVariance.Direction) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Constructs a SemiVariance with the specified Direction property
and default (true) biasCorrected property
- SemiVariance(boolean, SemiVariance.Direction) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Constructs a SemiVariance with the specified isBiasCorrected
property and the specified Direction property.
- SemiVariance(SemiVariance) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Copy constructor, creates a new SemiVariance identical
to the original
- SemiVariance.Direction - Enum in org.apache.commons.math.stat.descriptive.moment
-
The direction of the semivariance - either upside or downside.
- SemiVariance.Direction(boolean) - Constructor for enum org.apache.commons.math.stat.descriptive.moment.SemiVariance.Direction
-
Create a Direction with the given value.
- separator - Variable in class org.apache.commons.math.geometry.Vector3DFormat
-
Separator.
- separator - Variable in class org.apache.commons.math.linear.RealVectorFormat
-
Separator.
- sequence - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
step size sequence.
- serializeRealMatrix(RealMatrix, ObjectOutputStream) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- serializeRealVector(RealVector, ObjectOutputStream) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- serialVersionUID - Static variable in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
-
serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.analysis.interpolation.NevilleInterpolator
-
serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Serialization identifier
- serialVersionUID - Static variable in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.ArgumentOutsideDomainException
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.complex.Complex
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.complex.ComplexField
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.complex.ComplexFormat
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.ConvergenceException
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.DimensionMismatchException
-
Deprecated.
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractDistribution
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.FDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.TDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.DuplicateSampleAbscissaException
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.estimation.EstimationException
-
Deprecated.
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.ConvergenceException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.DimensionMismatchException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.MathIllegalNumberException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.MathIllegalStateException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.MathInternalError
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.NoDataException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.NotPositiveException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.NotStrictlyPositiveException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.NullArgumentException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.NumberIsTooLargeException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.NumberIsTooSmallException
-
Serializable version Id.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.OutOfRangeException
-
Serializable version Id.
- serialVersionUID - Static variable in class org.apache.commons.math.exception.util.DummyLocalizable
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.exception.ZeroException
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.AbstractFormat
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.BigFraction
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.BigFractionField
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.BigFractionFormat
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.Fraction
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.fraction.FractionConversionException
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.FractionField
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.FractionFormat
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.ProperBigFractionFormat
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.fraction.ProperFractionFormat
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.FunctionEvaluationException
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.genetics.InvalidRepresentationException
-
Serialization version id
- serialVersionUID - Static variable in exception org.apache.commons.math.geometry.CardanEulerSingularityException
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.geometry.NotARotationMatrixException
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.geometry.Rotation
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.geometry.Vector3D
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.geometry.Vector3DFormat
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.linear.ArrayFieldVector
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.linear.ArrayRealVector
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Serialization id
- serialVersionUID - Static variable in class org.apache.commons.math.linear.BlockFieldMatrix
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.linear.BlockRealMatrix
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.linear.InvalidMatrixException
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.linear.MatrixIndexException
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.linear.MatrixVisitorException
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.linear.NonSquareMatrixException
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.linear.NotPositiveDefiniteMatrixException
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.linear.NotSymmetricMatrixException
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.linear.OpenMapRealVector
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.linear.RealVectorFormat
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.linear.SingularMatrixException
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.linear.SparseFieldMatrix
-
Serial id
- serialVersionUID - Static variable in class org.apache.commons.math.linear.SparseFieldVector
-
Serial version id
- serialVersionUID - Static variable in exception org.apache.commons.math.MathConfigurationException
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.MathException
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.MathRuntimeException
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.MaxEvaluationsExceededException
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.MaxIterationsExceededException
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.ode.ContinuousOutputModel
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.ode.DerivativeException
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.ode.events.EventException
-
Serialization UID.
- serialVersionUID - Static variable in exception org.apache.commons.math.ode.events.EventState.EmbeddedDerivativeException
-
Serializable UID.
- serialVersionUID - Static variable in exception org.apache.commons.math.ode.events.EventState.EmbeddedEventException
-
Serializable UID.
- serialVersionUID - Static variable in exception org.apache.commons.math.ode.IntegratorException
-
Serializable version identifier
- serialVersionUID - Static variable in exception org.apache.commons.math.ode.MultistepIntegrator.InitializationCompletedMarkerException
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaStepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.EulerStepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.GillStepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerStepInterpolator
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54StepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointStepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesStepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.fitting.GaussianDerivativeFunction
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.fitting.ParametricGaussianFunction
-
Serializable version Id.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
-
Serializable version id.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.linear.LinearConstraint
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.optimization.linear.NoFeasibleSolutionException
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.optimization.linear.UnboundedSolutionException
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Serializable version identifier.
- serialVersionUID - Static variable in exception org.apache.commons.math.optimization.OptimizationException
-
Deprecated.
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.RealPointValuePair
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.AbstractWell
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.random.JDKRandomGenerator
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.MersenneTwister
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.RandomAdaptor
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.RandomDataImpl
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.random.UniformRandomGenerator
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.Well1024a
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.Well19937a
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.Well19937c
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.Well44497a
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.Well44497b
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.random.Well512a
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.stat.clustering.Cluster
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics.AggregatingSummaryStatistics
-
The serialization version of this class
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Serialization UID
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Serialization UID
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Max
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Median
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Min
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
Serialization id
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.Product
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Serialization UID
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Serialization UID
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Serialization UID
- serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Serialization UID
- serialVersionUID - Static variable in class org.apache.commons.math.stat.Frequency.NaturalComparator
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.Frequency
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.stat.regression.SimpleRegression
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.transform.FastFourierTransformer.RootsOfUnity
-
Serializable version id.
- serialVersionUID - Static variable in class org.apache.commons.math.transform.FastFourierTransformer
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.util.BigReal
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.util.BigRealField
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.util.CompositeFormat
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.util.DefaultTransformer
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Serializable version identifier.
- serialVersionUID - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
-
Serializable version identifier
- serialVersionUID - Static variable in class org.apache.commons.math.util.TransformerMap
-
Serializable version identifier
- set(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Set all elements to a single value.
- set(int, ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set a set of consecutive elements.
- set(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set all elements to a single value.
- set(int, ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set a set of consecutive elements.
- set(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set all elements to a single value.
- set(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Set all elements to a single value.
- set(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Set all elements to a single value.
- set(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Set all elements to a single value.
- set(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Set all elements to a single value.
- set(Complex, int...) - Method in class org.apache.commons.math.transform.FastFourierTransformer.MultiDimensionalComplexMatrix
-
Set a matrix element.
- SET_QUANTILE_METHOD_NAME - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Name of the setQuantile method.
- setAbsoluteAccuracy(double) - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Set the absolute accuracy.
- setAbsoluteAccuracy(double) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Set the absolute accuracy.
- setAbsoluteAccuracy(double) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Set the absolute accuracy.
- setAlpha(double) - Method in interface org.apache.commons.math.distribution.BetaDistribution
-
- setAlpha(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setAlpha(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
-
- setAlpha(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setAlphaInternal(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Modify the shape parameter, alpha.
- setArity(int) - Method in class org.apache.commons.math.genetics.TournamentSelection
-
Sets the arity (number of chromosomes drawn to the tournament).
- setBeta(double) - Method in interface org.apache.commons.math.distribution.BetaDistribution
-
- setBeta(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setBeta(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
-
- setBeta(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setBetaInternal(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Modify the scale parameter, beta.
- setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Sets the biasCorrected property.
- setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
- setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
- setBound(boolean) - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Set the bound flag of the parameter
- setBrightnessExponent(int) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
-
Set the brightness exponent.
- setChiSquareTest(TTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0 - not compatible with use from multiple threads
- setChiSquareTest(ChiSquareTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0 - not compatible with use from multiple threads
- setChromosomes(List<Chromosome>) - Method in class org.apache.commons.math.genetics.ListPopulation
-
Sets the list of chromosomes.
- setColumn(int, T[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, T[]) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, double[]) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, T[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, RealVector) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in column number column
as a vector.
- setContractionCriteria(float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the contraction criteria for this ExpandContractDoubleArray.
- setConvergence(double) - Method in class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Set the convergence criterion threshold.
- setConvergenceChecker(RealConvergenceChecker) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Set the convergence checker.
- setConvergenceChecker(VectorialConvergenceChecker) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set the convergence checker.
- setConvergenceChecker(VectorialConvergenceChecker) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Set the convergence checker.
- setConvergenceChecker(VectorialConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Set the convergence checker.
- setCostRelativeTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Set the desired relative error in the sum of squares.
- setCostRelativeTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the desired relative error in the sum of squares.
- setData(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Set the data array.
- setData(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Set the data array.
- setData(double[]) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Set the data array.
- setData(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Set the data array.
- setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
-
- setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.TDistribution
-
- setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setDegreesOfFreedomInternal(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Modify the degrees of freedom.
- setDegreesOfFreedomInternal(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Modify the degrees of freedom.
- setDenominatorDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.FDistribution
-
- setDenominatorDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setDenominatorDegreesOfFreedomInternal(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Modify the denominator degrees of freedom.
- setDenominatorFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.AbstractFormat
-
Modify the denominator format.
- setDistribution(ChiSquaredDistribution) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Modify the distribution used to compute inference statistics.
- setDistribution(TDistribution) - Method in class org.apache.commons.math.stat.inference.TTestImpl
-
Deprecated.
in 2.2 (to be removed in 3.0).
- setDistribution(TDistribution) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Deprecated.
in 2.2 (to be removed in 3.0).
- setElement(int, double) - Method in interface org.apache.commons.math.util.DoubleArray
-
Sets the element at the specified index.
- setElement(int, double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the element at the specified index.
- setElitismRate(double) - Method in class org.apache.commons.math.genetics.ElitisticListPopulation
-
Sets the elitism rate, i.e.
- setEntry(int, int, T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, T) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set a single element.
- setEntry(int, double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set a single element.
- setEntry(int, int, T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Set a single element.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Set a single element.
- setEntry(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Set the entry in the specified row and column.
- setEntry(int, double) - Method in interface org.apache.commons.math.linear.RealVector
-
Set a single element.
- setEntry(int, int, T) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Set a single element.
- setEntry(int, int, double) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Set an entry of the tableau.
- setEquations(FirstOrderDifferentialEquations) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Set the differential equations.
- setEstimate(double) - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Set a new estimated value for the parameter.
- setExpansionFactor(float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the expansionFactor.
- setExpansionMode(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the expansionMode.
- setExponent(double) - Method in interface org.apache.commons.math.distribution.ZipfDistribution
-
- setExponent(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setExponentInternal(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Set the exponent characterising the distribution.
- setFunctionValue(double) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Set the value at the optimum.
- setFunctionValueAccuracy(double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Set the function value accuracy.
- setFunctionValueAccuracy(double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Set the function value accuracy.
- setGamma(GammaDistribution) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setGammaInternal(GammaDistribution) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Modify the underlying gamma distribution.
- setGeoMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the geometric mean.
- setGeoMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the geometric mean.
- setGeoMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the geometric mean.
- setGeoMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the geometric mean.
- setGeometricMeanImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the gemoetric mean.
- setIEEEFlags(int) - Method in class org.apache.commons.math.dfp.DfpField
-
Sets the IEEE 854 status flags.
- setIEEEFlagsBits(int) - Method in class org.apache.commons.math.dfp.DfpField
-
Sets some bits in the IEEE 854 status flags, without changing the already set bits.
- setIgnored(boolean) - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Set the ignore flag to the specified value
Setting the ignore flag to true allow to reject wrong
measurements, which sometimes can be detected only rather late.
- setImaginaryCharacter(String) - Method in class org.apache.commons.math.complex.ComplexFormat
-
Modify the imaginaryCharacter.
- setImaginaryFormat(NumberFormat) - Method in class org.apache.commons.math.complex.ComplexFormat
-
Modify the imaginaryFormat.
- setImpl(StorelessUnivariateStatistic[], StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets statistics implementations.
- setIndex(int) - Method in class org.apache.commons.math.linear.RealVector.Entry
-
Set the index of the entry.
- setInitialCapacity(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the initial capacity.
- setInitialStep(double) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
Set the initial step used to bracket the optimum in line search.
- setInitialStepBoundFactor(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Set the positive input variable used in determining the initial step bound.
- setInitialStepBoundFactor(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the positive input variable used in determining the initial step bound.
- setInitialStepSize(double) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Set the initial step size.
- setInterpolatedTime(double) - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Set the time of the interpolated point.
- setInterpolatedTime(double) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians.StepInterpolatorWrapper
-
Deprecated.
Set the time of the interpolated point.
- setInterpolatedTime(double) - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Set the time of the interpolated point.
- setInterpolatedTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Set the time of the interpolated point.
- setInterpolatedTime(double) - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Set the time of the interpolated point.
- setInterpolationControl(boolean, int) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Set the interpolation order control parameter.
- setKurtosisImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the kurtosis.
- setLineSearchSolver(UnivariateRealSolver) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
Set the solver to use during line search.
- setMaxCostEval(int) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Set the maximal number of cost evaluations allowed.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Set the maximal number of differential equations function evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Set the maximal number of differential equations function evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Set the maximal number of differential equations function evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxGrowth(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Set the maximal growth factor for stepsize control.
- setMaxGrowth(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Set the maximal growth factor for stepsize control.
- setMaximalIterationCount(int) - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Set the upper limit for the number of iterations.
- setMaximalIterationCount(int) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Set the upper limit for the number of iterations.
- setMaximalIterationCount(int) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Set the upper limit for the number of iterations.
- setMaxImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the maximum.
- setMaxImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the maximum.
- setMaxImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the maximum.
- setMaxImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the maximum.
- setMaxImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the maximum.
- setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMean(double) - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
-
- setMean(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setMean(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
-
- setMean(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setMean(double) - Method in interface org.apache.commons.math.distribution.PoissonDistribution
-
- setMean(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setMeanImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the mean.
- setMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the mean.
- setMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the mean.
- setMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the mean.
- setMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the mean.
- setMeanInternal(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Modify the mean.
- setMeanInternal(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Modify the mean.
- setMedian(double) - Method in interface org.apache.commons.math.distribution.CauchyDistribution
-
- setMedian(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setMedianInternal(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Modify the median.
- setMicropshereElements(int) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
-
Set the number of microsphere elements.
- setMinimalIterationCount(int) - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
-
Set the lower limit for the number of iterations.
- setMinimalIterationCount(int) - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Set the lower limit for the number of iterations.
- setMinImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the minimum.
- setMinImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the minimum.
- setMinImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the minimum.
- setMinImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the minimum.
- setMinImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the minimum.
- setMinReduction(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Set the minimal reduction factor for stepsize control.
- setMinReduction(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Set the minimal reduction factor for stepsize control.
- setMode(int) - Method in class org.apache.commons.math.random.ValueServer
-
Setter for property mode.
- setMu(double) - Method in class org.apache.commons.math.random.ValueServer
-
Setter for property mu.
- setNoIntercept(boolean) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
- setNormal(NormalDistribution) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNormalAndMeanInternal(NormalDistribution, double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Set the Poisson mean for the distribution.
- setNumberOfElements(int) - Method in interface org.apache.commons.math.distribution.ZipfDistribution
-
- setNumberOfElements(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumberOfElementsInternal(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Set the number of elements (e.g.
- setNumberOfSuccesses(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
- setNumberOfSuccesses(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumberOfSuccesses(int) - Method in interface org.apache.commons.math.distribution.PascalDistribution
-
- setNumberOfSuccesses(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumberOfSuccessesInternal(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Modify the number of successes.
- setNumberOfSuccessesInternal(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Change the number of successes for this distribution.
- setNumberOfTrials(int) - Method in interface org.apache.commons.math.distribution.BinomialDistribution
-
- setNumberOfTrials(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumberOfTrialsInternal(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Change the number of trials for this distribution.
- setNumElements(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
This function allows you to control the number of elements contained
in this array, and can be used to "throw out" the last n values in an
array.
- setNumeratorDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.FDistribution
-
- setNumeratorDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumeratorDegreesOfFreedomInternal(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Modify the numerator degrees of freedom.
- setNumeratorFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.AbstractFormat
-
Modify the numerator format.
- setOneWayAnova(OneWayAnova) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0 - not compatible with use from multiple threads
- setOrderControl(int, double, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Set the order control parameters.
- setOrthoTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Set the desired max cosine on the orthogonality.
- setOrthoTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the desired max cosine on the orthogonality.
- setParameter(int, double) - Method in interface org.apache.commons.math.ode.jacobians.ParameterizedODE
-
Deprecated.
Set a parameter.
- setParRelativeTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Set the desired relative error in the approximate solution parameters.
- setParRelativeTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the desired relative error in the approximate solution parameters.
- setPercentileImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
- setPopulationLimit(int) - Method in class org.apache.commons.math.genetics.ListPopulation
-
Sets the maximal population size.
- setPopulationSize(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
- setPopulationSize(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setPopulationSizeInternal(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Modify the population size.
- setPreconditioner(Preconditioner) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
Set the preconditioner.
- setProbabilityOfSuccess(double) - Method in interface org.apache.commons.math.distribution.BinomialDistribution
-
- setProbabilityOfSuccess(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setProbabilityOfSuccess(double) - Method in interface org.apache.commons.math.distribution.PascalDistribution
-
- setProbabilityOfSuccess(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setProbabilityOfSuccessInternal(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Change the probability of success for this distribution.
- setProbabilityOfSuccessInternal(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Change the probability of success for this distribution.
- setQRRankingThreshold(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the desired threshold for QR ranking.
- setQuantile(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Sets the value of the quantile field (determines what percentile is
computed when evaluate() is called with no quantile argument).
- setRandomGenerator(RandomGenerator) - Static method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Set the (static) random generator.
- setRealFormat(NumberFormat) - Method in class org.apache.commons.math.complex.ComplexFormat
-
Modify the realFormat.
- setRelativeAccuracy(double) - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Set the relative accuracy.
- setRelativeAccuracy(double) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Set the relative accuracy.
- setRelativeAccuracy(double) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Set the relative accuracy.
- setResult(double, int) - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Convenience function for implementations.
- setResult(double, int) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Convenience function for implementations.
- setResult(double, double, int) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Convenience function for implementations.
- setResult(double, double, int) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Deprecated.
in 2.2 (no alternative).
- setRoundingMode(DfpField.RoundingMode) - Method in class org.apache.commons.math.dfp.DfpField
-
Set the rounding mode.
- setRoundingMode(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Sets the rounding mode for decimal divisions.
- setRoundingMode(RoundingMode) - Method in class org.apache.commons.math.util.BigReal
-
Sets the rounding mode for decimal divisions.
- setRow(int, T[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, T[]) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, double[]) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, T[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, RealVector) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in row number row
as a vector.
- setSafety(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Set the safety factor for stepsize control.
- setSafety(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Set the safety factor for stepsize control.
- setSampleSize(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
- setSampleSize(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setSampleSizeInternal(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Modify the sample size.
- setScale(double) - Method in interface org.apache.commons.math.distribution.CauchyDistribution
-
- setScale(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setScale(double) - Method in interface org.apache.commons.math.distribution.WeibullDistribution
-
- setScale(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setScale(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Sets the scale for division operations.
- setScale(int) - Method in class org.apache.commons.math.util.BigReal
-
Sets the scale for division operations.
- setScaleInternal(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Modify the scale parameter.
- setScaleInternal(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Modify the scale parameter.
- setSecureAlgorithm(String, String) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Sets the PRNG algorithm for the underlying SecureRandom instance using
the Security Provider API.
- setSeed(int) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Sets the seed of the underlying random number generator using an
int seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Sets the seed of the underlying random number generator using an
int array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Sets the seed of the underyling random number generator using a
long seed.
- setSeed(int) - Method in class org.apache.commons.math.random.AbstractWell
-
Reinitialize the generator as if just built with the given int seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.AbstractWell
-
Reinitialize the generator as if just built with the given int array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.AbstractWell
-
Reinitialize the generator as if just built with the given long seed.
- setSeed(int) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Sets the seed of the underlying random number generator using an
int seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Sets the seed of the underlying random number generator using an
int array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Sets the seed of the underlying random number generator using a
long seed.
- setSeed(int) - Method in class org.apache.commons.math.random.JDKRandomGenerator
-
Sets the seed of the underlying random number generator using an
int seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.JDKRandomGenerator
-
Sets the seed of the underlying random number generator using an
int array seed.
- setSeed(int) - Method in class org.apache.commons.math.random.MersenneTwister
-
Reinitialize the generator as if just built with the given int seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.MersenneTwister
-
Reinitialize the generator as if just built with the given int array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.MersenneTwister
-
Reinitialize the generator as if just built with the given long seed.
- setSeed(int) - Method in class org.apache.commons.math.random.RandomAdaptor
-
Sets the seed of the underlying random number generator using an
int seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.RandomAdaptor
-
Sets the seed of the underlying random number generator using an
int array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.RandomAdaptor
-
Sets the seed of the underlying random number generator using a
long seed.
- setSeed(int) - Method in interface org.apache.commons.math.random.RandomGenerator
-
Sets the seed of the underlying random number generator using an
int seed.
- setSeed(int[]) - Method in interface org.apache.commons.math.random.RandomGenerator
-
Sets the seed of the underlying random number generator using an
int array seed.
- setSeed(long) - Method in interface org.apache.commons.math.random.RandomGenerator
-
Sets the seed of the underlying random number generator using a
long seed.
- setShape(double) - Method in interface org.apache.commons.math.distribution.WeibullDistribution
-
- setShape(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setShapeInternal(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Modify the shape parameter.
- setSigma(double) - Method in class org.apache.commons.math.random.ValueServer
-
Setter for property sigma.
- setSkewnessImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the skewness.
- setSoftCurrentTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Restrict step range to a limited part of the global step.
- setSoftPreviousTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Restrict step range to a limited part of the global step.
- setStabilityCheck(boolean, int, int, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Set the stability check controls.
- setStandardDeviation(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
-
- setStandardDeviation(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setStandardDeviationInternal(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Modify the standard deviation.
- setStartConfiguration(double[]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set start configuration for simplex.
- setStartConfiguration(double[][]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set start configuration for simplex.
- setStarterIntegrator(FirstOrderIntegrator) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Set the starter integrator.
- setStateInitialized(boolean) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Set the stateInitialized flag.
- setSteadyStateThreshold(double) - Method in class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Set the steady state detection threshold.
- setStepsizeControl(double, double, double, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Set the step size control factors.
- setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(BigDecimal[][], int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(T[][], int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(double[][], int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Replace the submatrix starting at row, column using data in
the input subMatrix array.
- setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Set a set of consecutive elements.
- setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Set a set of consecutive elements.
- setSubVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set a set of consecutive elements.
- setSubVector(int, T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set a set of consecutive elements.
- setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set a set of consecutive elements.
- setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set a set of consecutive elements.
- setSubVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Set a set of consecutive elements.
- setSubVector(int, T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Set a set of consecutive elements.
- setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Set a set of consecutive elements.
- setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Set a set of consecutive elements.
- setSubVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Set a set of consecutive elements.
- setSubVector(int, double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Set a set of consecutive elements.
- setSubVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Set a set of consecutive elements.
- setSubVector(int, T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Set a set of consecutive elements.
- setSumImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the sum.
- setSumImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the Sum.
- setSumImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the Sum.
- setSumImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the Sum.
- setSumImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the Sum.
- setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Sets the implementation for the sum of logs.
- setSumLogImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the sum of logs.
- setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the sum of logs.
- setSumLogImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the sum of logs.
- setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the sum of logs.
- setSumsqImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the sum of squares.
- setSumsqImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the sum of squares.
- setSumsqImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the sum of squares.
- setSumsqImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the sum of squares.
- setSumsqImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the sum of squares.
- setUnknownDistributionChiSquareTest(UnknownDistributionChiSquareTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0 - not compatible with use from multiple threads
- setup(UnivariateRealFunction) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
-
Checks to see if f is null, throwing IllegalArgumentException if so.
- setValue(double) - Method in class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
-
Set the value of the entry.
- setValue(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
-
Set the value of the entry.
- setValue(double) - Method in class org.apache.commons.math.linear.RealVector.Entry
-
Set the value of the entry.
- setValuesFileURL(String) - Method in class org.apache.commons.math.random.ValueServer
-
Sets the valuesFileURL using a string URL representation
- setValuesFileURL(URL) - Method in class org.apache.commons.math.random.ValueServer
-
Sets the valuesFileURL
- setVarianceDirection(SemiVariance.Direction) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Sets the variance direction
- setVarianceImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the variance.
- setVarianceImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the variance.
- setVarianceImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the variance.
- setWholeFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
-
Modify the whole format.
- setWholeFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.ProperFractionFormat
-
Modify the whole format.
- setWindowSize(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
WindowSize controls the number of values which contribute
to the reported statistics.
- setWindowSize(int) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
WindowSize controls the number of values which contribute
to the reported statistics.
- SGN_MASK - Static variable in class org.apache.commons.math.util.MathUtils
-
Offset to order signed double numbers lexicographically.
- SGN_MASK_FLOAT - Static variable in class org.apache.commons.math.util.MathUtils
-
Offset to order signed double numbers lexicographically.
- shape - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
The shape parameter.
- shift() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Shift one step forward.
- shiftLeft() - Method in class org.apache.commons.math.dfp.Dfp
-
Shift the mantissa left, and adjust the exponent to compensate.
- shiftRight() - Method in class org.apache.commons.math.dfp.Dfp
-
Shift the mantissa right, and adjust the exponent to compensate.
- shouldContract() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns true if the internal storage array has too many unused
storage positions.
- shouldGrowTable() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Check if tables should grow due to increased size.
- shouldGrowTable() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Check if tables should grow due to increased size.
- shuffle(int[], int) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Uses a 2-cycle permutation shuffle to randomly re-order the last elements
of list.
- sigma - Variable in class org.apache.commons.math.optimization.direct.NelderMead
-
Shrinkage coefficient.
- sigma - Variable in class org.apache.commons.math.random.ValueServer
-
Standard deviation for use with GAUSSIAN_MODE.
- sign - Variable in class org.apache.commons.math.dfp.Dfp
-
Sign bit: & for positive, -1 for negative.
- sign(byte) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for byte value
x.
- sign(double) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for double precision
x.
- sign(float) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for float value
x.
- sign(int) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for int value
x.
- sign(long) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for long value
x.
- sign(short) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for short value
x.
- SIGNUM - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- signum(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the signum of a number.
- signum(float) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the signum of a number.
- SimpleEstimationProblem - Class in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- SimpleEstimationProblem() - Constructor for class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Build an empty instance without parameters nor measurements.
- SimpleRealPointChecker - Class in org.apache.commons.math.optimization
-
- SimpleRealPointChecker() - Constructor for class org.apache.commons.math.optimization.SimpleRealPointChecker
-
Build an instance with default threshold.
- SimpleRealPointChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleRealPointChecker
-
Build an instance with a specified threshold.
- SimpleRegression - Class in org.apache.commons.math.stat.regression
-
Estimates an ordinary least squares regression model
with one independent variable.
- SimpleRegression() - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
-
Create an empty SimpleRegression instance
- SimpleRegression(TDistribution) - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
-
- SimpleRegression(int) - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
-
Create an empty SimpleRegression.
- SimpleScalarValueChecker - Class in org.apache.commons.math.optimization
-
- SimpleScalarValueChecker() - Constructor for class org.apache.commons.math.optimization.SimpleScalarValueChecker
-
Build an instance with default threshold.
- SimpleScalarValueChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleScalarValueChecker
-
Build an instance with a specified threshold.
- SimpleVectorialPointChecker - Class in org.apache.commons.math.optimization
-
- SimpleVectorialPointChecker() - Constructor for class org.apache.commons.math.optimization.SimpleVectorialPointChecker
-
Build an instance with default threshold.
- SimpleVectorialPointChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleVectorialPointChecker
-
Build an instance with a specified threshold.
- SimpleVectorialValueChecker - Class in org.apache.commons.math.optimization
-
- SimpleVectorialValueChecker() - Constructor for class org.apache.commons.math.optimization.SimpleVectorialValueChecker
-
Build an instance with default threshold.
- SimpleVectorialValueChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleVectorialValueChecker
-
Build an instance with a specified threshold.
- simplex - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Simplex.
- SimplexSolver - Class in org.apache.commons.math.optimization.linear
-
Solves a linear problem using the Two-Phase Simplex Method.
- SimplexSolver() - Constructor for class org.apache.commons.math.optimization.linear.SimplexSolver
-
Build a simplex solver with default settings.
- SimplexSolver(double) - Constructor for class org.apache.commons.math.optimization.linear.SimplexSolver
-
Build a simplex solver with a specified accepted amount of error
- SimplexTableau - Class in org.apache.commons.math.optimization.linear
-
A tableau for use in the Simplex method.
- SimplexTableau(LinearObjectiveFunction, Collection<LinearConstraint>, GoalType, boolean, double) - Constructor for class org.apache.commons.math.optimization.linear.SimplexTableau
-
Build a tableau for a linear problem.
- SimpsonIntegrator - Class in org.apache.commons.math.analysis.integration
-
Implements the
Simpson's Rule for integration of real univariate functions.
- SimpsonIntegrator(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.integration.SimpsonIntegrator
-
- SimpsonIntegrator() - Constructor for class org.apache.commons.math.analysis.integration.SimpsonIntegrator
-
Construct an integrator.
- SIN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- sin() - Method in class org.apache.commons.math.complex.Complex
-
Compute the
sine
of this complex number.
- sin(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the sine of the argument.
- sin(double) - Static method in class org.apache.commons.math.util.FastMath
-
Sine function.
- SINE_TABLE_A - Static variable in class org.apache.commons.math.util.FastMath
-
Sine table (high bits).
- SINE_TABLE_B - Static variable in class org.apache.commons.math.util.FastMath
-
Sine table (low bits).
- singular - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Singularity indicator.
- singular - Variable in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
-
Singularity indicator.
- singular - Variable in class org.apache.commons.math.linear.LUDecompositionImpl
-
Singularity indicator.
- singular - Variable in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
-
Singularity indicator.
- SingularMatrixException - Exception in org.apache.commons.math.linear
-
Thrown when a matrix is singular.
- SingularMatrixException() - Constructor for exception org.apache.commons.math.linear.SingularMatrixException
-
Construct an exception with a default message.
- SingularValueDecomposition - Interface in org.apache.commons.math.linear
-
An interface to classes that implement an algorithm to calculate the
Singular Value Decomposition of a real matrix.
- SingularValueDecompositionImpl - Class in org.apache.commons.math.linear
-
Calculates the compact Singular Value Decomposition of a matrix.
- SingularValueDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Calculates the compact Singular Value Decomposition of the given matrix.
- SingularValueDecompositionImpl.Solver - Class in org.apache.commons.math.linear
-
Specialized solver.
- SingularValueDecompositionImpl.Solver(double[], RealMatrix, RealMatrix, boolean) - Constructor for class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
-
Build a solver from decomposed matrix.
- singularValues - Variable in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Singular values.
- SINH - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- sinh() - Method in class org.apache.commons.math.complex.Complex
-
- sinh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the hyperbolic sine of a number.
- sinh(double) - Static method in class org.apache.commons.math.util.MathUtils
-
- sinInternal(Dfp[]) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Computes sin(a) Used when 0 < a < pi/4.
- sinQ(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute sine over the first quadrant (0 < x < pi/2).
- size - Variable in class org.apache.commons.math.util.MultidimensionalCounter
-
Counter sizes.
- size - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Current size of the map.
- size() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Get the number of elements stored in the map.
- size - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Current size of the map.
- size() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Get the number of elements stored in the map.
- Skewness - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes the skewness of the available values.
- Skewness() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Constructs a Skewness
- Skewness(ThirdMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Constructs a Skewness with an external moment
- Skewness(Skewness) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Copy constructor, creates a new Skewness identical
to the original
- skewnessImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Skewness statistic implementation - can be reset by setter.
- slowCos(double, double[]) - Static method in class org.apache.commons.math.util.FastMath
-
For x between 0 and pi/4 compute cosine
- slowexp(double, double[]) - Static method in class org.apache.commons.math.util.FastMath
-
For x between 0 and 1, returns exp(x), uses extended precision
- slowLog(double) - Static method in class org.apache.commons.math.util.FastMath
-
xi in the range of [1, 2].
- slowSin(double, double[]) - Static method in class org.apache.commons.math.util.FastMath
-
For x between 0 and pi/4 compute sine.
- smooth(double[], double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
Compute a weighted loess fit on the data at the original abscissae.
- smooth(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
Compute a loess fit on the data at the original abscissae.
- SmoothingBicubicSplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
-
- SmoothingBicubicSplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingBicubicSplineInterpolator
-
Deprecated.
- SmoothingPolynomialBicubicSplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
-
Generates a bicubic interpolation function.
- SmoothingPolynomialBicubicSplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
Default constructor.
- SmoothingPolynomialBicubicSplineInterpolator(int) - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
- SmoothingPolynomialBicubicSplineInterpolator(int, int) - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
- SNAN - Static variable in class org.apache.commons.math.dfp.Dfp
-
Indicator value for signaling NaN.
- softCurrentTime - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
soft current time
- softPreviousTime - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
soft previous time
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Deprecated.
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Deprecated.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Solve for a zero in the given interval, start at startValue.
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Solve for a zero root in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Deprecated.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Find a zero in the given interval with an initial guess.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Find a zero in the given interval.
- solve(UnivariateRealFunction, double, double, double, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Find a zero starting search according to the three provided points.
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Find a real root in the given interval with initial value.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Find a real root in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(Complex[], Complex) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Find a real root in the given interval with initial value.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Find a real root in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Find a zero near the midpoint of min and max.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Find a zero near the value startValue.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Find a root in the given interval with initial value.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Find a root in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Find a zero in the given interval.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Find a zero in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
- solve(UnivariateRealFunction, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
- solve(UnivariateRealFunction, double, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Solve for a zero root in the given interval.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Solve for a zero in the given interval, start at startValue.
- solve(UnivariateRealFunction, double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
-
Convenience method to find a zero of a univariate real function.
- solve(UnivariateRealFunction, double, double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
-
Convenience method to find a zero of a univariate real function.
- solve(double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Deprecated.
- solve(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Deprecated.
- solve(BigDecimal[]) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the solution vector for a linear system with coefficient
matrix = this and constant vector = b.
- solve(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns a matrix of (column) solution vectors for linear systems with
coefficient matrix = this and constant vectors = columns of
b.
- solve(BigDecimal[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a matrix of (column) solution vectors for linear systems with
coefficient matrix = this and constant vectors = columns of
b.
- solve(double[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a matrix of (column) solution vectors for linear systems with
coefficient matrix = this and constant vectors = columns of
b.
- solve(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a matrix of (column) solution vectors for linear systems with
coefficient matrix = this and constant vectors = columns of
b.
- solve(double[]) - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(RealVector) - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(ArrayRealVector) - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
-
Solve the linear equation A × X = B.
- solve(RealMatrix) - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(double[]) - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(RealVector) - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(RealMatrix) - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(double[]) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
-
Solve the linear equation A × X = B for symmetric matrices A.
- solve(RealVector) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
-
Solve the linear equation A × X = B for symmetric matrices A.
- solve(RealMatrix) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl.Solver
-
Solve the linear equation A × X = B for symmetric matrices A.
- solve(T[]) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(T[]) - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(FieldVector<T>) - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
-
Solve the linear equation A × X = B.
- solve(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(double[]) - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(RealVector) - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(ArrayRealVector) - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
-
Solve the linear equation A × X = B.
- solve(RealMatrix) - Method in class org.apache.commons.math.linear.LUDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(double[]) - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(RealVector) - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(ArrayRealVector) - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
-
Solve the linear equation A × X = B.
- solve(RealMatrix) - Method in class org.apache.commons.math.linear.QRDecompositionImpl.Solver
-
Solve the linear equation A × X = B for matrices A.
- solve(double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
- solve(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
- solve(double[]) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
-
Solve the linear equation A × X = B in least square sense.
- solve(RealVector) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
-
Solve the linear equation A × X = B in least square sense.
- solve(RealMatrix) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl.Solver
-
Solve the linear equation A × X = B in least square sense.
- solve2(double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
- solve2(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solveAll(double[], double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
- solveAll(Complex[], Complex) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
- solvedCols - Variable in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Number of solved variables.
- solvedCols - Variable in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Number of solved point.
- solvePhase1(SimplexTableau) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
-
Solves Phase 1 of the Simplex method.
- solver - Variable in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
solver to use in the line search (may be null).
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Solver absolute accuracy for inverse cumulative computation
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Inverse cumulative probability accuracy
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Inverse cumulative probability accuracy
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Inverse cumulative probability accuracy
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Inverse cumulative probability accuracy
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.FDistributionImpl
-
Inverse cumulative probability accuracy
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Inverse cumulative probability accuracy
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Inverse cumulative probability accuracy
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.TDistributionImpl
-
Inverse cumulative probability accuracy
- solverAbsoluteAccuracy - Variable in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Inverse cumulative probability accuracy
- sortedRepresentation - Variable in class org.apache.commons.math.genetics.RandomKey
-
Cache of sorted representation (unmodifiable).
- sortObservations() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Sort the observations with respect to the abscissa.
- source - Variable in class org.apache.commons.math.exception.util.DummyLocalizable
-
Source string.
- sourceFormat - Variable in enum org.apache.commons.math.exception.util.LocalizedFormats
-
Source English format.
- SparseFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
Sparse matrix implementation based on an open addressed map.
- SparseFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
-
Creates a matrix with no data.
- SparseFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
-
Create a new SparseFieldMatrix with the supplied row and column dimensions.
- SparseFieldMatrix(SparseFieldMatrix<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
-
Copy constructor.
- SparseFieldMatrix(FieldMatrix<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
-
Generic copy constructor.
- SparseFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
- SparseFieldVector(Field<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Build a 0-length vector.
- SparseFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Construct a (dimension)-length vector of zeros.
- SparseFieldVector(SparseFieldVector<T>, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Build a resized vector, for use with append.
- SparseFieldVector(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Build a vector with known the sparseness (for advanced use only).
- SparseFieldVector(Field<T>, T[]) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Create from a Field array.
- SparseFieldVector(SparseFieldVector<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Copy constructor.
- sparseIterator() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Specialized implementations may choose to not iterate over all
dimensions, either because those values are unset, or are equal
to defaultValue(), or are small enough to be ignored for the
purposes of iteration.
- sparseIterator() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Specialized implementations may choose to not iterate over all
dimensions, either because those values are unset, or are equal
to defaultValue(), or are small enough to be ignored for the
purposes of iteration.
- sparseIterator() - Method in interface org.apache.commons.math.linear.RealVector
-
Specialized implementations may choose to not iterate over all
dimensions, either because those values are unset, or are equal
to defaultValue(), or are small enough to be ignored for the
purposes of iteration.
- SparseRealMatrix - Interface in org.apache.commons.math.linear
-
Marker interface for
RealMatrix implementations that require sparse backing storage
- SparseRealVector - Interface in org.apache.commons.math.linear
-
Marker interface for RealVectors that require sparse backing storage
- SpearmansCorrelation - Class in org.apache.commons.math.stat.correlation
-
Spearman's rank correlation.
- SpearmansCorrelation(RealMatrix, RankingAlgorithm) - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Create a SpearmansCorrelation with the given input data matrix
and ranking algorithm.
- SpearmansCorrelation(RealMatrix) - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Create a SpearmansCorrelation from the given data matrix.
- SpearmansCorrelation() - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Create a SpearmansCorrelation without data.
- specific - Variable in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Pattern used to build the message (specific context).
- specific - Variable in exception org.apache.commons.math.exception.MathIllegalStateException
-
Pattern used to build the message (specific context).
- specific - Variable in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Pattern used to build the message (specific context).
- SplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
-
Computes a natural (also known as "free", "unclamped") cubic spline interpolation for the data set.
- SplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.SplineInterpolator
-
- splines - Variable in class org.apache.commons.math.analysis.interpolation.BicubicSplineInterpolatingFunction
-
Set of cubic splines patching the whole data grid
- splines - Variable in class org.apache.commons.math.analysis.interpolation.TricubicSplineInterpolatingFunction
-
Set of cubic splines pacthing the whole data grid
- split(String) - Method in class org.apache.commons.math.dfp.DfpField
-
Breaks a string representation up into two
Dfp's.
- split(DfpField, String) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Breaks a string representation up into two dfp's.
- split(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Splits a
Dfp into 2
Dfp's such that their sum is equal to the input
Dfp.
- split(double, double[]) - Static method in class org.apache.commons.math.util.FastMath
-
Compute split[0], split[1] such that their sum is equal to d,
and split[0] has its 30 least significant bits as zero.
- splitAdd(double[], double[], double[]) - Static method in class org.apache.commons.math.util.FastMath
-
Add two numbers in split form.
- splitDiv(Dfp[], Dfp[]) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Divide two numbers that are split in to two pieces that are meant to be added together.
- splitMult(Dfp[], Dfp[]) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Multiply two numbers that are split in to two pieces that are
meant to be added together.
- splitMult(double[], double[], double[]) - Static method in class org.apache.commons.math.util.FastMath
-
Multiply two numbers in split form.
- splitPow(Dfp[], int) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Raise a split base to the a power.
- splitReciprocal(double[], double[]) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the reciprocal of in.
- sqr2 - Variable in class org.apache.commons.math.dfp.DfpField
-
- sqr2Reciprocal - Variable in class org.apache.commons.math.dfp.DfpField
-
- sqr2ReciprocalString - Static variable in class org.apache.commons.math.dfp.DfpField
-
High precision string representation of √2 / 2.
- sqr2Split - Variable in class org.apache.commons.math.dfp.DfpField
-
A two elements
Dfp array with value √2 split in two pieces.
- sqr2String - Static variable in class org.apache.commons.math.dfp.DfpField
-
High precision string representation of √2.
- sqr3 - Variable in class org.apache.commons.math.dfp.DfpField
-
- sqr3Reciprocal - Variable in class org.apache.commons.math.dfp.DfpField
-
- sqr3ReciprocalString - Static variable in class org.apache.commons.math.dfp.DfpField
-
High precision string representation of √3 / 3.
- sqr3String - Static variable in class org.apache.commons.math.dfp.DfpField
-
High precision string representation of √3.
- SQRT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- sqrt() - Method in class org.apache.commons.math.complex.Complex
-
- sqrt() - Method in class org.apache.commons.math.dfp.Dfp
-
Compute the square root.
- sqrt(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the square root of a number.
- sqrt1z() - Method in class org.apache.commons.math.complex.Complex
-
Compute the
square root of 1 -
this2 for this complex
number.
- SQRT2PI - Static variable in class org.apache.commons.math.distribution.NormalDistributionImpl
-
&sqrt;(2 π)
- SQRT3 - Static variable in class org.apache.commons.math.random.UniformRandomGenerator
-
Square root of three.
- SQRT_TRAP - Static variable in class org.apache.commons.math.dfp.Dfp
-
Name for traps triggered by square root.
- stabilityReduction - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
stepsize reduction factor in case of stability check failure.
- stage(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.analysis.integration.LegendreGaussIntegrator
-
Compute the n-th stage integral.
- stage(UnivariateRealFunction, double, double, int) - Method in class org.apache.commons.math.analysis.integration.TrapezoidIntegrator
-
Compute the n-th stage integral of trapezoid rule.
- standardDeviation - Variable in class org.apache.commons.math.distribution.NormalDistributionImpl
-
The standard deviation of this distribution.
- standardDeviation - Variable in class org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
-
Standard deviation vector.
- StandardDeviation - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes the sample standard deviation.
- StandardDeviation() - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Constructs a StandardDeviation.
- StandardDeviation(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Constructs a StandardDeviation from an external second moment.
- StandardDeviation(StandardDeviation) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Copy constructor, creates a new StandardDeviation identical
to the original
- StandardDeviation(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Contructs a StandardDeviation with the specified value for the
isBiasCorrected property.
- StandardDeviation(boolean, SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Contructs a StandardDeviation with the specified value for the
isBiasCorrected property and the supplied external moment.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultFieldMatrixChangingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultFieldMatrixPreservingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultRealMatrixChangingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultRealMatrixPreservingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrixChangingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrixPreservingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.MatrixUtils.BigFractionMatrixConverter
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.MatrixUtils.FractionMatrixConverter
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrixChangingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrixPreservingVisitor
-
Start visiting a matrix.
- start(double, double[], double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Start the integration.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator.Corrector
-
Start visiting a matrix.
- start() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns the starting index of the internal array.
- startConfiguration - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Start simplex configuration.
- starter - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
Starter integrator.
- startIndex - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
The position of the first addressable element in the internal storage
array.
- starts - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Number of starts to go.
- starts - Variable in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Number of starts to go.
- starts - Variable in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Number of starts to go.
- starts - Variable in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Number of starts to go.
- states - Variable in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Events states.
- states - Variable in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
States table.
- states - Variable in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
States table.
- statesInitialized - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Initialization indicator of events states.
- stateVariation - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
State variation.
- STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
-
Internal weights Butcher array.
- STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Internal weights Butcher array.
- STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Internal weights Butcher array.
- STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
-
Internal weights Butcher array.
- STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
-
Internal weights Butcher array.
- STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
-
Internal weights Butcher array.
- STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
-
Internal weights Butcher array.
- STATIC_A - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
-
Internal weights Butcher array.
- STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
-
Propagation weights Butcher array.
- STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Propagation weights Butcher array.
- STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Propagation weights Butcher array.
- STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
-
Propagation weights Butcher array.
- STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
-
Propagation weights Butcher array.
- STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
-
Propagation weights Butcher array.
- STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
-
Propagation weights Butcher array.
- STATIC_B - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
-
Propagation weights Butcher array.
- STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
-
Time steps Butcher array.
- STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Time steps Butcher array.
- STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Time steps Butcher array.
- STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.EulerIntegrator
-
Time steps Butcher array.
- STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.GillIntegrator
-
Time steps Butcher array.
- STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
-
Time steps Butcher array.
- STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.MidpointIntegrator
-
Time steps Butcher array.
- STATIC_C - Static variable in class org.apache.commons.math.ode.nonstiff.ThreeEighthesIntegrator
-
Time steps Butcher array.
- STATIC_E - Static variable in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
-
Error weights Butcher array.
- StatisticalMultivariateSummary - Interface in org.apache.commons.math.stat.descriptive
-
Reporting interface for basic multivariate statistics.
- StatisticalSummary - Interface in org.apache.commons.math.stat.descriptive
-
Reporting interface for basic univariate statistics.
- StatisticalSummaryValues - Class in org.apache.commons.math.stat.descriptive
-
Value object representing the results of a univariate statistical summary.
- StatisticalSummaryValues(double, double, long, double, double, double) - Constructor for class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
Constructor
- statistics - Variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
The SummaryStatistics in which aggregate statistics are accumulated.
- statisticsPrototype - Variable in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
A SummaryStatistics serving as a prototype for creating SummaryStatistics
contributing to this aggregate
- StatUtils - Class in org.apache.commons.math.stat
-
StatUtils provides static methods for computing statistics based on data
stored in double[] arrays.
- StatUtils() - Constructor for class org.apache.commons.math.stat.StatUtils
-
Private Constructor
- steadyStateThreshold - Variable in class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Threshold for cost steady state detection.
- step - Variable in class org.apache.commons.math.ode.nonstiff.RungeKuttaIntegrator
-
Integration step.
- stepAccepted(double, double[]) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Inform the event handlers that the step has been accepted
by the integrator.
- stepAccepted(double, double[]) - Method in class org.apache.commons.math.ode.events.EventState
-
Acknowledge the fact the step has been accepted by the integrator.
- stepControl1 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
first stepsize control factor.
- stepControl2 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
second stepsize control factor.
- stepControl3 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
third stepsize control factor.
- stepControl4 - Variable in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
fourth stepsize control factor.
- StepHandler - Interface in org.apache.commons.math.ode.sampling
-
This interface represents a handler that should be called after
each successful step.
- stepHandlers - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Step handler.
- StepHandlerWithJacobians - Interface in org.apache.commons.math.ode.jacobians
-
Deprecated.
as of 2.2 the complete package is deprecated, it will be replaced
in 3.0 by a completely rewritten implementation
- StepInterpolator - Interface in org.apache.commons.math.ode.sampling
-
This interface represents an interpolator over the last step
during an ODE integration.
- StepInterpolatorWithJacobians - Interface in org.apache.commons.math.ode.jacobians
-
Deprecated.
as of 2.2 the complete package is deprecated, it will be replaced
in 3.0 by a completely rewritten implementation
- StepNormalizer - Class in org.apache.commons.math.ode.sampling
-
- StepNormalizer(double, FixedStepHandler) - Constructor for class org.apache.commons.math.ode.sampling.StepNormalizer
-
Simple constructor.
- steps - Variable in class org.apache.commons.math.ode.ContinuousOutputModel
-
Steps table.
- stepSize - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Current stepsize.
- stepStart - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Current step start time.
- stop() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Check if the integration should be stopped at the end of the
current step.
- STOP - Static variable in interface org.apache.commons.math.ode.events.EventHandler
-
Stop indicator.
- stop() - Method in class org.apache.commons.math.ode.events.EventState
-
Check if the integration should be stopped at the end of the
current step.
- STOP - Static variable in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
-
Deprecated.
Stop indicator.
- StoppingCondition - Interface in org.apache.commons.math.genetics
-
Algorithm used to determine when to stop evolution.
- store(double, Map.Entry<RealVector, Double>) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolatingFunction.MicrosphereSurfaceElement
-
Store the illumination and index of the brightest sample.
- storedData - Variable in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Stored data.
- StorelessUnivariateStatistic - Interface in org.apache.commons.math.stat.descriptive
-
- storeTime(double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54StepInterpolator
-
Store the current step time.
- storeTime(double) - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853StepInterpolator
-
Store the current step time.
- storeTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Store the current step time.
- strict - Variable in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
Whether the sequence must be strictly increasing or decreasing.
- stringValue - Variable in enum org.apache.commons.math.optimization.linear.Relationship
-
Display string for the relationship.
- subAndCheck(int, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Subtract two integers, checking for overflow.
- subAndCheck(long, long) - Static method in class org.apache.commons.math.util.MathUtils
-
Subtract two long integers, checking for overflow.
- substituteMostRecentElement(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Substitutes value for the most recently added value.
- SUBTRACT - Static variable in class org.apache.commons.math.analysis.BinaryFunction
-
Deprecated.
- subtract(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function subtracting another function from the instance.
- subtract(PolynomialFunction) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Subtract a polynomial from the instance.
- subtract(Complex) - Method in class org.apache.commons.math.complex.Complex
-
Return the difference between this complex number and the given complex
number.
- subtract(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Subtract x from this.
- subtract(T) - Method in interface org.apache.commons.math.FieldElement
-
Compute this - a.
- subtract(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
-
Subtracts the value of an BigInteger from the value of this one,
returning the result in reduced form.
- subtract(int) - Method in class org.apache.commons.math.fraction.BigFraction
-
Subtracts the value of an integer from the value of this one,
returning the result in reduced form.
- subtract(long) - Method in class org.apache.commons.math.fraction.BigFraction
-
Subtracts the value of an integer from the value of this one,
returning the result in reduced form.
- subtract(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
-
Subtracts the value of another fraction from the value of this one,
returning the result in reduced form.
- subtract(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
-
Subtracts the value of another fraction from the value of this one,
returning the result in reduced form.
- subtract(int) - Method in class org.apache.commons.math.fraction.Fraction
-
Subtract an integer from the fraction.
- subtract(Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
-
Subtract a vector from the instance.
- subtract(double, Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
-
Subtract a scaled vector from the instance.
- subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Compute this minus m.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Compute this minus m.
- subtract(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Subtract v from this vector.
- subtract(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Subtract v from this vector.
- subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Compute this minus m.
- subtract(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Compute this minus m.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Compute this minus m.
- subtract(Array2DRowRealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Compute this minus m.
- subtract(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute this minus v.
- subtract(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute this minus v.
- subtract(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute this minus v.
- subtract(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Subtract v from this vector.
- subtract(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Subtract v from this vector.
- subtract(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Compute this minus v.
- subtract(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Compute this minus m.
- subtract(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Compute this minus m.
- subtract(BigMatrixImpl) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Compute this minus m.
- subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Compute this minus m.
- subtract(BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Compute this minus m.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Compute this minus m.
- subtract(BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Compute this minus m.
- subtract(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Compute this minus m.
- subtract(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Compute this minus v.
- subtract(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Compute this minus v.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute this minus m.
- subtract(OpenMapRealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute this minus m.
- subtract(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to subtract OpenMapRealVectors.
- subtract(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Subtract v from this vector.
- subtract(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Subtract v from this vector.
- subtract(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Compute this minus m.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Compute this minus m.
- subtract(RealMatrixImpl) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Compute this minus m.
- subtract(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Subtract v from this vector.
- subtract(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Subtract v from this vector.
- subtract(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Optimized method to subtract SparseRealVectors.
- subtract(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Compute this minus v.
- subtract(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Compute this minus v.
- subtract(BigReal) - Method in class org.apache.commons.math.util.BigReal
-
Compute this - a.
- subtractRow(int, int, double) - Method in class org.apache.commons.math.optimization.linear.SimplexTableau
-
Subtracts a multiple of one row from another.
- suffix - Variable in class org.apache.commons.math.geometry.Vector3DFormat
-
Suffix.
- suffix - Variable in class org.apache.commons.math.linear.RealVectorFormat
-
Suffix.
- sum - Variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
The sum of the sample values
- Sum - Class in org.apache.commons.math.stat.descriptive.summary
-
Returns the sum of the available values.
- Sum() - Constructor for class org.apache.commons.math.stat.descriptive.summary.Sum
-
Create a Sum instance
- Sum(Sum) - Constructor for class org.apache.commons.math.stat.descriptive.summary.Sum
-
Copy constructor, creates a new Sum identical
to the original
- sum - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
sum of values that have been added
- SUM - Static variable in class org.apache.commons.math.stat.StatUtils
-
sum
- sum(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the values in the input array, or
Double.NaN if the array is empty.
- sum(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- SUM_OF_LOGS - Static variable in class org.apache.commons.math.stat.StatUtils
-
sumLog
- SUM_OF_SQUARES - Static variable in class org.apache.commons.math.stat.StatUtils
-
sumSq
- sumDifference(double[], double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the (signed) differences between corresponding elements of the
input arrays -- i.e., sum(sample1[i] - sample2[i]).
- sumImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sum statistic implementation - can be reset by setter.
- sumImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sum statistic implementation - can be reset by setter.
- sumImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sum statistic implementation - can be reset by setter.
- sumLog - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
sumLog of values that have been added
- sumLog(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the natural logs of the entries in the input array, or
Double.NaN if the array is empty.
- sumLog(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the natural logs of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- sumLogImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sum of log statistic implementation - can be reset by setter.
- sumLogImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sum of log statistic implementation - can be reset by setter.
- SummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
Computes summary statistics for a stream of data values added using the
addValue method.
- SummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Construct a SummaryStatistics instance
- SummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
A copy constructor.
- sumOfLogs - Variable in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Wrapped SumOfLogs instance
- SumOfLogs - Class in org.apache.commons.math.stat.descriptive.summary
-
Returns the sum of the natural logs for this collection of values.
- SumOfLogs() - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Create a SumOfLogs instance
- SumOfLogs(SumOfLogs) - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Copy constructor, creates a new SumOfLogs identical
to the original
- SumOfSquares - Class in org.apache.commons.math.stat.descriptive.summary
-
Returns the sum of the squares of the available values.
- SumOfSquares() - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Create a SumOfSquares instance
- SumOfSquares(SumOfSquares) - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Copy constructor, creates a new SumOfSquares identical
to the original
- sums - Variable in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Sums for each component.
- sumsq - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
sum of the square of each value that has been added
- sumSq(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the squares of the entries in the input array, or
Double.NaN if the array is empty.
- sumSq(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the squares of the entries in the specified portion of
the input array, or Double.NaN if the designated subarray
is empty.
- sumsqImpl - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sum of squares statistic implementation - can be reset by setter.
- sumSqImpl - Variable in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sum of squares statistic implementation - can be reset by setter.
- sumsqImpl - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sum of squares statistic implementation - can be reset by setter.
- sumX - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
-
sum of x values
- sumXX - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
-
total variation in x (sum of squared deviations from xbar)
- sumXY - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
-
sum of products
- sumY - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
-
sum of y values
- sumYY - Variable in class org.apache.commons.math.stat.regression.SimpleRegression
-
total variation in y (sum of squared deviations from ybar)
- SynchronizedDescriptiveStatistics - Class in org.apache.commons.math.stat.descriptive
-
- SynchronizedDescriptiveStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Construct an instance with infinite window
- SynchronizedDescriptiveStatistics(int) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Construct an instance with finite window
- SynchronizedDescriptiveStatistics(SynchronizedDescriptiveStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
A copy constructor.
- SynchronizedMultivariateSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
- SynchronizedMultivariateSummaryStatistics(int, boolean) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Construct a SynchronizedMultivariateSummaryStatistics instance
- SynchronizedSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
Implementation of
SummaryStatistics that
is safe to use in a multithreaded environment.
- SynchronizedSummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Construct a SynchronizedSummaryStatistics instance
- SynchronizedSummaryStatistics(SynchronizedSummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
A copy constructor.