Index (Apache Commons Math 4.0-beta1)

A B C D E F G H I J K L M N O P Q R S T U V W Z
All Classes All Packages

A

aarstAndVanLaarhoven(double) - Static method in interface org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing.CoolingSchedule: Aarst and van Laarhoven (1985) scheme: \[ T_{i + 1} = \frac{T_{i}}{1 + \frac{T_i \ln(1 + \delta)}{3 \sigma}} \]
ABOVE_SIDE - org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: Only solutions for which values are greater than or equal to zero are acceptable as solutions for root-finding.
abs() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: absolute value.
abs() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: absolute value.
abs() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Get the absolute value of instance.
abs() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: absolute value.
abs(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Absolute value.
abs(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
abs(float) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Absolute value.
abs(float) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
abs(int) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Absolute value.
abs(int) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
abs(long) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Absolute value.
abs(long) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
Abs - Class in org.apache.commons.math4.legacy.analysis.function: Absolute value function.
Abs() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Abs
AbstractConvergenceChecker<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class for all convergence checker implementations.
AbstractConvergenceChecker(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.AbstractConvergenceChecker: Build an instance with a specified thresholds.
AbstractCurveFitter - Class in org.apache.commons.math4.legacy.fitting: Base class that contains common code for fitting parametric univariate real functions y = f(p_i;x), where x is the independent variable and the p_i are the parameters.
AbstractCurveFitter() - Constructor for class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter
AbstractCurveFitter.TheoreticalValuesFunction - Class in org.apache.commons.math4.legacy.fitting: Vector function for computing function theoretical values.
AbstractEvaluation - Class in org.apache.commons.math4.legacy.fitting.leastsquares: An implementation of LeastSquaresProblem.Evaluation that is designed for extension.
AbstractFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: Base class managing common boilerplate for all integrators.
AbstractFieldIntegrator(Field<T>, String) - Constructor for class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Build an instance.
AbstractFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Basic implementation of FieldMatrix methods regardless of the underlying storage.
AbstractFieldMatrix() - Constructor for class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Constructor for use with Serializable.
AbstractFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Creates a matrix with no data.
AbstractFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Create a new FieldMatrix<T> with the supplied row and column dimensions.
AbstractFieldStepInterpolator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.sampling: This abstract class represents an interpolator over the last step during an ODE integration.
AbstractFieldStepInterpolator(boolean, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Simple constructor.
AbstractIntegerDistribution - Class in org.apache.commons.math4.legacy.distribution: Base class for integer-valued discrete distributions.
AbstractIntegerDistribution() - Constructor for class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution
AbstractIntegrator - Class in org.apache.commons.math4.legacy.ode: Base class managing common boilerplate for all integrators.
AbstractIntegrator() - Constructor for class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Build an instance with a null name.
AbstractIntegrator(String) - Constructor for class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Build an instance.
AbstractListChromosome<T> - Class in org.apache.commons.math4.legacy.genetics: Chromosome represented by an immutable list of a fixed length.
AbstractListChromosome(List<T>) - Constructor for class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Constructor, copying the input representation.
AbstractListChromosome(List<T>, boolean) - Constructor for class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Constructor.
AbstractListChromosome(T[]) - Constructor for class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Constructor, copying the input representation.
AbstractMultipleLinearRegression - Class in org.apache.commons.math4.legacy.stat.regression: Abstract base class for implementations of MultipleLinearRegression.
AbstractMultipleLinearRegression() - Constructor for class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression
AbstractMultivariateRealDistribution - Class in org.apache.commons.math4.legacy.distribution: Base class for multivariate probability distributions.
AbstractMultivariateRealDistribution(int) - Constructor for class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution
AbstractOptimizationProblem<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class for implementing optimization problems.
AbstractOptimizationProblem(int, int, ConvergenceChecker<PAIR>) - Constructor for class org.apache.commons.math4.legacy.optim.AbstractOptimizationProblem: Create an AbstractOptimizationProblem from the given data.
AbstractParameterizable - Class in org.apache.commons.math4.legacy.ode: This abstract class provides boilerplate parameters list.
AbstractParameterizable(String...) - Constructor for class org.apache.commons.math4.legacy.ode.AbstractParameterizable: Simple constructor.
AbstractParameterizable(Collection<String>) - Constructor for class org.apache.commons.math4.legacy.ode.AbstractParameterizable: Simple constructor.
AbstractPolynomialSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Base class for solvers.
AbstractPolynomialSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver: Construct a solver with given absolute accuracy.
AbstractPolynomialSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver: Construct a solver with given accuracies.
AbstractPolynomialSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver: Construct a solver with given accuracies.
AbstractRealDistribution - Class in org.apache.commons.math4.legacy.distribution: Base class for probability distributions on the reals.
AbstractRealDistribution() - Constructor for class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution
AbstractRealMatrix - Class in org.apache.commons.math4.legacy.linear: Basic implementation of RealMatrix methods regardless of the underlying storage.
AbstractRealMatrix() - Constructor for class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Creates a matrix with no data.
AbstractRealMatrix(int, int) - Constructor for class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Create a new RealMatrix with the supplied row and column dimensions.
AbstractStepInterpolator - Class in org.apache.commons.math4.legacy.ode.sampling: This abstract class represents an interpolator over the last step during an ODE integration.
AbstractStepInterpolator() - Constructor for class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Simple constructor.
AbstractStepInterpolator(double[], boolean, EquationsMapper, EquationsMapper[]) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Simple constructor.
AbstractStepInterpolator(AbstractStepInterpolator) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Copy constructor.
AbstractStorelessUnivariateStatistic - Class in org.apache.commons.math4.legacy.stat.descriptive: Abstract base class for implementations of the StorelessUnivariateStatistic interface.
AbstractStorelessUnivariateStatistic() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic
AbstractUnivariateDifferentiableSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Provide a default implementation for several functions useful to generic solvers.
AbstractUnivariateDifferentiableSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateDifferentiableSolver: Construct a solver with given absolute accuracy.
AbstractUnivariateDifferentiableSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateDifferentiableSolver: Construct a solver with given accuracies.
AbstractUnivariateSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Base class for solvers.
AbstractUnivariateSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateSolver: Construct a solver with given absolute accuracy.
AbstractUnivariateSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateSolver: Construct a solver with given accuracies.
AbstractUnivariateSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateSolver: Construct a solver with given accuracies.
AbstractUnivariateStatistic - Class in org.apache.commons.math4.legacy.stat.descriptive: Abstract base class for implementations of the UnivariateStatistic interface.
AbstractUnivariateStatistic() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic
acceptStep(AbstractFieldStepInterpolator<T>, T) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Accept a step, triggering events and step handlers.
acceptStep(AbstractStepInterpolator, double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Accept a step, triggering events and step handlers.
AccurateMath - Class in org.apache.commons.math4.core.jdkmath: Portable alternative to Math and StrictMath.
acos() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Arc cosine operation.
acos() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Arc cosine operation.
acos() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Arc cosine operation.
acos() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Arc cosine operation.
acos(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Compute the arc cosine of a number.
acos(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
acos(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute arc cosine of a derivative structure.
acos(Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpMath: computes the arc-cosine of the argument.
Acos - Class in org.apache.commons.math4.legacy.analysis.function: Arc-cosine function.
Acos() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Acos
acosh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Inverse hyperbolic cosine operation.
acosh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Inverse hyperbolic cosine operation.
acosh() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Inverse hyperbolic cosine operation.
acosh() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Inverse hyperbolic cosine operation.
acosh(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Compute the inverse hyperbolic cosine of a number.
acosh(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
acosh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute inverse hyperbolic cosine of a derivative structure.
Acosh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic arc-cosine function.
Acosh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Acosh
Action - Enum in org.apache.commons.math4.legacy.ode.events: Enumerate for actions to be performed when an event occurs during ODE integration.
AdamsBashforthFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements explicit Adams-Bashforth integrators for Ordinary Differential Equations.
AdamsBashforthFieldIntegrator(Field<T>, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsBashforthFieldIntegrator: Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsBashforthFieldIntegrator(Field<T>, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsBashforthFieldIntegrator: Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsBashforthIntegrator - Class in org.apache.commons.math4.legacy.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.math4.legacy.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.math4.legacy.ode.nonstiff.AdamsBashforthIntegrator: Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: Base class for Adams-Bashforth and Adams-Moulton integrators.
AdamsFieldIntegrator(Field<T>, String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsFieldIntegrator: Build an Adams integrator with the given order and step control parameters.
AdamsFieldIntegrator(Field<T>, String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsFieldIntegrator: Build an Adams integrator with the given order and step control parameters.
AdamsIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: Base class for Adams-Bashforth and Adams-Moulton integrators.
AdamsIntegrator(String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsIntegrator: Build an Adams integrator with the given order and step control parameters.
AdamsIntegrator(String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsIntegrator: Build an Adams integrator with the given order and step control parameters.
AdamsMoultonFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements implicit Adams-Moulton integrators for Ordinary Differential Equations.
AdamsMoultonFieldIntegrator(Field<T>, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsMoultonFieldIntegrator: Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsMoultonFieldIntegrator(Field<T>, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsMoultonFieldIntegrator: Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsMoultonIntegrator - Class in org.apache.commons.math4.legacy.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.math4.legacy.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.math4.legacy.ode.nonstiff.AdamsMoultonIntegrator: Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsNordsieckFieldTransformer<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: Transformer to Nordsieck vectors for Adams integrators.
AdamsNordsieckTransformer - Class in org.apache.commons.math4.legacy.ode.nonstiff: Transformer to Nordsieck vectors for Adams integrators.
AdaptiveStepsizeFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This abstract class holds the common part of all adaptive stepsize integrators for Ordinary Differential Equations.
AdaptiveStepsizeFieldIntegrator(Field<T>, String, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Build an integrator with the given stepsize bounds.
AdaptiveStepsizeFieldIntegrator(Field<T>, String, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Build an integrator with the given stepsize bounds.
AdaptiveStepsizeIntegrator - Class in org.apache.commons.math4.legacy.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.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Build an integrator with the given stepsize bounds.
AdaptiveStepsizeIntegrator(String, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Build an integrator with the given stepsize bounds.
add(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: '+' operator.
add(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: '+' operator.
add(double) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: '+' operator.
add(double) - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: '+' operator.
add(double[], boolean) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Replace i-th facet of the microsphere.
add(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Perform addition of two derivative structures.
add(double, double) - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Adds a point to the sample.
add(double, double, double) - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Adds a point to the sample.
add(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Compute this + a.
add(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Compute this + a.
add(UnivariateDifferentiableFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Adds functions.
add(PolynomialFunction) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Add a polynomial to the instance.
add(UnivariateFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Adds functions.
add(Dfp) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Add x to this.
add(FieldDenseMatrix<T>) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Addition.
add(WeightedObservedPoint) - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Adds a point to the sample.
add(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Add m to this matrix.
add(Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Compute the sum of this and m.
add(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the sum of this and v.
add(BigReal) - Method in class org.apache.commons.math4.legacy.linear.BigReal: Compute this + a.
add(BlockFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Compute the sum of this and m.
add(BlockRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Compute the sum of this matrix and m.
add(DiagonalMatrix) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Compute the sum of this and m.
add(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Compute the sum of this and m.
add(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Compute the sum of this and m.
add(FieldMatrix<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Compute the sum of this and m.
add(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the sum of this and v.
add(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Compute the sum of this and v.
add(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Compute the sum of this and v.
add(OpenMapRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Compute the sum of this matrix and m.
add(OpenMapRealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Optimized method to add two OpenMapRealVectors.
add(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the sum of this and m.
add(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the sum of this and m.
add(RealMatrix) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the sum of this and m.
add(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Compute the sum of this vector and v.
add(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Compute the sum of this vector and v.
add(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Compute the sum of this vector and v.
add(SparseFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Optimized method to add sparse vectors.
add(T) - Method in interface org.apache.commons.math4.legacy.core.FieldElement: Compute this + a.
Add - Class in org.apache.commons.math4.legacy.analysis.function: Add the two operands.
Add() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Add
addChromosome(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Add the given chromosome to the population.
addChromosome(Chromosome) - Method in interface org.apache.commons.math4.legacy.genetics.Population: Add the given chromosome to the population.
addChromosomes(Collection<Chromosome>) - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Add a Collection of chromosomes to this Population.
addData(double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Adds the observations represented by the elements in data.
addData(double, double) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Adds the observation (x,y) to the regression data set.
addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int) - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int, UnivariateSolver) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int, UnivariateSolver) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int, UnivariateSolver) - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Add an event handler to the integrator.
addEventHandler(FieldEventHandler<T>, double, double, int) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Add an event handler to the integrator.
addEventHandler(FieldEventHandler<T>, double, double, int) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Add an event handler to the integrator.
addEventHandler(FieldEventHandler<T>, double, double, int, BracketedRealFieldUnivariateSolver<T>) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Add an event handler to the integrator.
addEventHandler(FieldEventHandler<T>, double, double, int, BracketedRealFieldUnivariateSolver<T>) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Add an event handler to the integrator.
addExact(int, int) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Add two numbers, detecting overflows.
addExact(int, int) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
addExact(long, long) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Add two numbers, detecting overflows.
addExact(long, long) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
addInPlace(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Add in place.
addIterationListener(IterationListener) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Attaches a listener to this manager.
addLink(Neuron, Neuron) - Method in class org.apache.commons.math4.neuralnet.Network: Adds a link from neuron a to neuron b.
addMessage(Localizable, Object...) - Method in class org.apache.commons.math4.legacy.exception.util.ExceptionContext: Adds a message.
addObservation(double[], double) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Adds an observation to the regression model.
addObservation(double[], double) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Adds one observation to the regression model.
addObservation(double[], double) - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Adds one observation to the regression model.
addObservations(double[][], double[]) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Adds multiple observations to the model.
addObservations(double[][], double[]) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Adds a series of observations to the regression model.
addObservations(double[][], double[]) - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Adds a series of observations to the regression model.
addObserver(SimplexOptimizer.Observer) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.SimplexOptimizer: Register a callback.
addParameterJacobianProvider(ParameterJacobianProvider) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Add a parameter Jacobian provider.
addPoint(T) - Method in class org.apache.commons.math4.legacy.ml.clustering.Cluster: Add a point to this cluster.
addRule(Pair<T[], T[]>) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.BaseRuleFactory: Stores a rule.
addSamplePoint(double, double[]...) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.HermiteInterpolator: Add a sample point.
addSamplePoint(T, T[]...) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.FieldHermiteInterpolator: Add a sample point.
addSecondaryEquations(FieldSecondaryEquations<T>) - Method in class org.apache.commons.math4.legacy.ode.FieldExpandableODE: Add a set of secondary equations to be integrated along with the primary set.
addSecondaryEquations(SecondaryEquations) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Add a set of secondary equations to be integrated along with the primary set.
addStepHandler(FieldStepHandler<T>) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Add a step handler to this integrator.
addStepHandler(FieldStepHandler<T>) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Add a step handler to this integrator.
addStepHandler(StepHandler) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Add a step handler to this integrator.
addStepHandler(StepHandler) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Add a step handler to this integrator.
addStepHandler(StepHandler) - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Add a step handler to this integrator.
addToEntry(int, double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Change an entry at the specified index.
addToEntry(int, double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Change an entry at the specified index.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Change an entry in the specified row and column.
addValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Adds the value to the dataset.
addValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Add a value to the data.
addValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Adds the value to the dataset.
addValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Add a value to the data.
addValue(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Add an n-tuple to the data.
addValue(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Add an n-tuple to the data.
addValue(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Adds 1 to the frequency count for v.
advance(RealVector.Entry) - Method in class org.apache.commons.math4.legacy.linear.RealVector.SparseEntryIterator: Advance an entry up to the next nonzero one.
aggregate(Collection<? extends StatisticalSummary>) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Computes aggregate summary statistics.
AggregateSummaryStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: An aggregator for SummaryStatistics from several data sets or data set partitions.
AggregateSummaryStatistics() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Initializes a new AggregateSummaryStatistics with default statistics implementations.
AggregateSummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math4.legacy.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.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Initializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics.
AgrestiCoullInterval - Class in org.apache.commons.math4.legacy.stat.interval: Implements the Agresti-Coull method for creating a binomial proportion confidence interval.
AgrestiCoullInterval() - Constructor for class org.apache.commons.math4.legacy.stat.interval.AgrestiCoullInterval
AkimaSplineInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Computes a cubic spline interpolation for the data set using the Akima algorithm, as originally formulated by Hiroshi Akima in his 1970 paper "A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures." J.
AkimaSplineInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.AkimaSplineInterpolator: Uses the original Akima algorithm.
AkimaSplineInterpolator(boolean) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.AkimaSplineInterpolator
align(int) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Make our exp equal to the supplied one, this may cause rounding.
AllowedSolution - Enum in org.apache.commons.math4.legacy.analysis.solvers: The kinds of solutions that a (bracketed univariate real) root-finding algorithm may accept as solutions.
alongAxes(double[]) - Static method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: The start configuration for simplex is built from a box parallel to the canonical axes of the space.
AlternativeHypothesis - Enum in org.apache.commons.math4.legacy.stat.inference: Represents an alternative hypothesis for a hypothesis test.
anovaFValue(Collection<double[]>) - Method in class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Computes the ANOVA F-value for a collection of double[] arrays.
anovaPValue(Collection<double[]>) - Method in class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Computes the ANOVA P-value for a collection of double[] arrays.
anovaPValue(Collection<SummaryStatistics>, boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Computes the ANOVA P-value for a collection of SummaryStatistics.
anovaTest(Collection<double[]>, double) - Method in class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.
ANY_SIDE - org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: There are no additional side restriction on the solutions for root-finding.
AnyMatrix - Interface in org.apache.commons.math4.legacy.linear: Interface defining very basic matrix operations.
append(double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a new vector by appending a double to this vector.
append(double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Construct a new vector by appending a double to this vector.
append(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Construct a new vector by appending a double to this vector.
append(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending a vector to this vector.
append(ArrayRealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending a vector to this vector.
append(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending a vector to this vector.
append(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Construct a vector by appending a vector to this vector.
append(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Construct a vector by appending a vector to this vector.
append(OpenMapRealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Optimized method to append a OpenMapRealVector.
append(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a new vector by appending a vector to this vector.
append(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Construct a new vector by appending a vector to this vector.
append(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Construct a new vector by appending a vector to this vector.
append(SparseFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Construct a vector by appending a vector to this vector.
append(ContinuousOutputFieldModel<T>) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Append another model at the end of the instance.
append(ContinuousOutputModel) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Append another model at the end of the instance.
append(StorelessCovariance) - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Appends sc to this, effectively aggregating the computations in sc with this.
append(SimpleRegression) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Appends data from another regression calculation to this one.
append(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending a T to this vector.
append(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Construct a vector by appending a T to this vector.
append(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Construct a vector by appending a T to this vector.
apply(double[]) - Method in interface org.apache.commons.math4.transform.ComplexTransform: Returns the transform of the specified data set.
apply(double[]) - Method in class org.apache.commons.math4.transform.FastCosineTransform: Returns the transform of the specified data set.
apply(double[]) - Method in class org.apache.commons.math4.transform.FastFourierTransform: Returns the transform of the specified data set.
apply(double[]) - Method in class org.apache.commons.math4.transform.FastHadamardTransform: Returns the transform of the specified data set.
apply(double[]) - Method in class org.apache.commons.math4.transform.FastSineTransform: Returns the transform of the specified data set.
apply(double[]) - Method in interface org.apache.commons.math4.transform.RealTransform: Returns the transform of the specified data set.
apply(int[]) - Method in class org.apache.commons.math4.transform.FastHadamardTransform: Returns the forward transform of the given data set.
apply(DoubleUnaryOperator, double, double, int) - Method in interface org.apache.commons.math4.transform.ComplexTransform: Returns the transform of the specified function.
apply(DoubleUnaryOperator, double, double, int) - Method in class org.apache.commons.math4.transform.FastCosineTransform: Returns the transform of the specified function.
apply(DoubleUnaryOperator, double, double, int) - Method in class org.apache.commons.math4.transform.FastFourierTransform: Returns the transform of the specified function.
apply(DoubleUnaryOperator, double, double, int) - Method in class org.apache.commons.math4.transform.FastSineTransform: Returns the transform of the specified function.
apply(DoubleUnaryOperator, double, double, int) - Method in interface org.apache.commons.math4.transform.RealTransform: Returns the transform of the specified function.
apply(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Apply the given statistic to the data associated with this set of statistics.
apply(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Apply the given statistic to the data associated with this set of statistics.
apply(Complex[]) - Method in interface org.apache.commons.math4.transform.ComplexTransform: Returns the transform of the specified data set.
apply(Complex[]) - Method in class org.apache.commons.math4.transform.FastFourierTransform: Returns the transform of the specified data set.
applyAsDouble(double) - Method in interface org.apache.commons.math4.legacy.analysis.UnivariateFunction
applyAsDouble(double[], double[]) - Method in class org.apache.commons.math4.neuralnet.EuclideanDistance
applyAsDouble(double, double) - Method in interface org.apache.commons.math4.legacy.analysis.BivariateFunction
applyAsDouble(long) - Method in class org.apache.commons.math4.neuralnet.sofm.util.ExponentialDecayFunction: Computes a e^{-numCall / b}.
applyAsDouble(long) - Method in class org.apache.commons.math4.neuralnet.sofm.util.QuasiSigmoidDecayFunction: Computes the value of the learning factor.
approximateP(double, int, int) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
approximateP(double, int, int) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Uses the Kolmogorov-Smirnov distribution to approximate \(P(D_{n,m} > d)\) where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic.
ARGUMENT_OUTSIDE_DOMAIN - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ArgUtils - Class in org.apache.commons.math4.legacy.exception.util: Utility class for transforming the list of arguments passed to constructors of exceptions.
ARITHMETIC_EXCEPTION - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ARRAY_ELEMENT - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ARRAY_SIZE_EXCEEDS_MAX_VARIABLES - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ARRAY_SIZES_SHOULD_HAVE_DIFFERENCE_1 - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ARRAY_SUMS_TO_ZERO - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ARRAY_ZERO_LENGTH_OR_NULL_NOT_ALLOWED - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
Array2DRowFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Implementation of FieldMatrix<T> using a FieldElement[][] array to store entries.
Array2DRowFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Creates a matrix with no data.
Array2DRowFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> with the supplied row and column dimensions.
Array2DRowFieldMatrix(Field<T>, T[]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new (column) FieldMatrix<T> using v as the data for the unique column of the created matrix.
Array2DRowFieldMatrix(Field<T>, T[][]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowFieldMatrix(Field<T>, T[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowFieldMatrix(T[]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new (column) FieldMatrix<T> using v as the data for the unique column of the created matrix.
Array2DRowFieldMatrix(T[][]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowFieldMatrix(T[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowRealMatrix - Class in org.apache.commons.math4.legacy.linear: Implementation of RealMatrix using a double[][] array to store entries.
Array2DRowRealMatrix() - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Creates a matrix with no data.
Array2DRowRealMatrix(double[]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new (column) RealMatrix using v as the data for the unique column of the created matrix.
Array2DRowRealMatrix(double[][]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new RealMatrix using the input array as the underlying data array.
Array2DRowRealMatrix(double[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new RealMatrix using the input array as the underlying data array.
Array2DRowRealMatrix(int, int) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new RealMatrix with the supplied row and column dimensions.
ArrayFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: This class implements the FieldVector interface with a FieldElement array.
ArrayFieldVector(int, T) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector with preset values.
ArrayFieldVector(Field<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Build a 0-length vector.
ArrayFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector of zeroes.
ArrayFieldVector(Field<T>, T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from an array, copying the input array.
ArrayFieldVector(Field<T>, T[], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Create a new ArrayFieldVector using the input array as the underlying data array.
ArrayFieldVector(Field<T>, T[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from part of a array.
ArrayFieldVector(Field<T>, T[], T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayFieldVector(ArrayFieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from another vector, using a deep copy.
ArrayFieldVector(ArrayFieldVector<T>, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from another vector.
ArrayFieldVector(FieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from another vector, using a deep copy.
ArrayFieldVector(FieldVector<T>, FieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayFieldVector(FieldVector<T>, T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayFieldVector(T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from an array, copying the input array.
ArrayFieldVector(T[], boolean) - Constructor for class org.apache.commons.math4.legacy.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.math4.legacy.linear.ArrayFieldVector: Construct a vector from part of a array.
ArrayFieldVector(T[], FieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayFieldVector(T[], T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayRealVector - Class in org.apache.commons.math4.legacy.linear: This class implements the RealVector interface with a double array.
ArrayRealVector() - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Build a 0-length vector.
ArrayRealVector(double[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from an array, copying the input array.
ArrayRealVector(double[], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Create a new ArrayRealVector using the input array as the underlying data array.
ArrayRealVector(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(double[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from part of a array.
ArrayRealVector(double[], ArrayRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector of zeroes.
ArrayRealVector(int, double) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector with preset values.
ArrayRealVector(Double[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from an array.
ArrayRealVector(Double[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from part of an array.
ArrayRealVector(ArrayRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from another vector, using a deep copy.
ArrayRealVector(ArrayRealVector, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from another vector.
ArrayRealVector(ArrayRealVector, double[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(ArrayRealVector, ArrayRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(ArrayRealVector, RealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(RealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from another vector, using a deep copy.
ArrayRealVector(RealVector, ArrayRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
asin() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Arc sine operation.
asin() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Arc sine operation.
asin() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Arc sine operation.
asin() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Arc sine operation.
asin(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Compute the arc sine of a number.
asin(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
asin(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute arc sine of a derivative structure.
asin(Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpMath: computes the arc-sine of the argument.
Asin - Class in org.apache.commons.math4.legacy.analysis.function: Arc-sine function.
Asin() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Asin
asinh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Inverse hyperbolic sine operation.
asinh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Inverse hyperbolic sine operation.
asinh() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Inverse hyperbolic sine operation.
asinh() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Inverse hyperbolic sine operation.
asinh(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Compute the inverse hyperbolic sine of a number.
asinh(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
asinh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute inverse hyperbolic sine of a derivative structure.
Asinh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic arc-sine function.
Asinh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Asinh
asList() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Creates a (deep) copy of the simplex points.
ASSYMETRIC_EIGEN_NOT_SUPPORTED - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
AT_LEAST_ONE_COLUMN - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
AT_LEAST_ONE_ROW - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
atan() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Arc tangent operation.
atan() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Arc tangent operation.
atan() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Arc tangent operation.
atan() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Arc tangent operation.
atan(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Arctangent function.
atan(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
atan(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute arc tangent of a derivative structure.
atan(Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpMath: Computes the arc tangent of the argument.
Atan - Class in org.apache.commons.math4.legacy.analysis.function: Arc-tangent function.
Atan() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Atan
atan2(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute two arguments arc tangent of a derivative structure.
atan2(double, double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Two arguments arctangent function.
atan2(double, double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
atan2(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Two arguments arc tangent operation.
atan2(DerivativeStructure, DerivativeStructure) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Two arguments arc tangent operation.
atan2(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Two arguments arc tangent operation.
atan2(SparseGradient, SparseGradient) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Two arguments arc tangent operation.
atan2(Dfp) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Two arguments arc tangent operation.
atan2(T) - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Two arguments arc tangent operation.
Atan2 - Class in org.apache.commons.math4.legacy.analysis.function: Arc-tangent function.
Atan2() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Atan2
atanh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Inverse hyperbolic tangent operation.
atanh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Inverse hyperbolic tangent operation.
atanh() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Inverse hyperbolic tangent operation.
atanh() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Inverse hyperbolic tangent operation.
atanh(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Compute the inverse hyperbolic tangent of a number.
atanh(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
atanh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute inverse hyperbolic tangent of a derivative structure.
Atanh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic arc-tangent function.
Atanh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Atanh
atanInternal(Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpMath: computes the arc-tangent of the argument.
AVERAGE - org.apache.commons.math4.legacy.stat.ranking.TiesStrategy: Ties get the average of applicable ranks.

B

BANDWIDTH - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
BASE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
BaseAbstractUnivariateIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration: Provide a default implementation for several generic functions.
BaseAbstractUnivariateIntegrator(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Construct an integrator with given accuracies.
BaseAbstractUnivariateIntegrator(double, double, int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Construct an integrator with given accuracies and iteration counts.
BaseAbstractUnivariateIntegrator(int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Construct an integrator with given iteration counts.
BaseAbstractUnivariateSolver<FUNC extends UnivariateFunction> - Class in org.apache.commons.math4.legacy.analysis.solvers: Provide a default implementation for several functions useful to generic solvers.
BaseAbstractUnivariateSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Construct a solver with given absolute accuracy.
BaseAbstractUnivariateSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Construct a solver with given accuracies.
BaseAbstractUnivariateSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Construct a solver with given accuracies.
BaseMultiStartMultivariateOptimizer<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class multi-start optimizer for a multivariate function.
BaseMultiStartMultivariateOptimizer(BaseMultivariateOptimizer<PAIR>, int, Supplier<double[]>) - Constructor for class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Create a multi-start optimizer from a single-start optimizer.
BaseMultivariateOptimizer<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class for implementing optimizers for multivariate functions.
BaseMultivariateOptimizer(ConvergenceChecker<PAIR>) - Constructor for class org.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer
BaseOptimizer<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class for implementing optimizers.
BaseOptimizer(ConvergenceChecker<PAIR>) - Constructor for class org.apache.commons.math4.legacy.optim.BaseOptimizer
BaseOptimizer(ConvergenceChecker<PAIR>, int, int) - Constructor for class org.apache.commons.math4.legacy.optim.BaseOptimizer
BaseRuleFactory<T extends Number> - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Base class for rules that determines the integration nodes and their weights.
BaseRuleFactory() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.BaseRuleFactory
BaseSecantSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Base class for all bracketing Secant-based methods for root-finding (approximating a zero of a univariate real function).
BaseSecantSolver(double, double, double, BaseSecantSolver.Method) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Construct a solver.
BaseSecantSolver(double, double, BaseSecantSolver.Method) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Construct a solver.
BaseSecantSolver(double, BaseSecantSolver.Method) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Construct a solver.
BaseSecantSolver.Method - Enum in org.apache.commons.math4.legacy.analysis.solvers: Secant-based root-finding methods.
BaseUnivariateSolver<FUNC extends UnivariateFunction> - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (univariate real) rootfinding algorithms.
BELOW_SIDE - org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: Only solutions for which values are less than or equal to zero are acceptable as solutions for root-finding.
BESSEL_FUNCTION_BAD_ARGUMENT - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
BESSEL_FUNCTION_FAILED_CONVERGENCE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
BesselJ - Class in org.apache.commons.math4.legacy.special: This class provides computation methods related to Bessel functions of the first kind.
BesselJ(double) - Constructor for class org.apache.commons.math4.legacy.special.BesselJ: Create a new BesselJ with the given order.
BesselJ.BesselJResult - Class in org.apache.commons.math4.legacy.special: Encapsulates the results returned by BesselJ.rjBesl(double, double, int).
BesselJResult(double[], int) - Constructor for class org.apache.commons.math4.legacy.special.BesselJ.BesselJResult: Create a new BesselJResult with the given values and valid value count.
BicubicInterpolatingFunction - Class in org.apache.commons.math4.legacy.analysis.interpolation: Function that implements the bicubic spline interpolation.
BicubicInterpolatingFunction(double[], double[], double[][], double[][], double[][], double[][]) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
BicubicInterpolatingFunction(double[], double[], double[][], double[][], double[][], double[][], boolean) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
BicubicInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Generates a bicubic interpolating function.
BicubicInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolator: Default constructor.
BicubicInterpolator(boolean) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolator: Creates an interpolator.
bigDecimalValue() - Method in class org.apache.commons.math4.legacy.linear.BigReal: Get the BigDecimal value corresponding to the instance.
BigReal - Class in org.apache.commons.math4.legacy.linear: Arbitrary precision decimal number.
BigReal(char[]) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a characters representation.
BigReal(char[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a characters representation.
BigReal(char[], int, int, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a characters representation.
BigReal(char[], MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a characters representation.
BigReal(double) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a double.
BigReal(double, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a double.
BigReal(int) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from an int.
BigReal(int, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from an int.
BigReal(long) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a long.
BigReal(long, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a long.
BigReal(String) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a String representation.
BigReal(String, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a String representation.
BigReal(BigDecimal) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a BigDecimal.
BigReal(BigInteger) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a BigInteger.
BigReal(BigInteger, int) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from an unscaled BigInteger.
BigReal(BigInteger, int, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from an unscaled BigInteger.
BigReal(BigInteger, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a BigInteger.
BigRealField - Class in org.apache.commons.math4.legacy.linear: Representation of real numbers with arbitrary precision field.
BinaryChromosome - Class in org.apache.commons.math4.legacy.genetics: Chromosome represented by a vector of 0s and 1s.
BinaryChromosome(Integer[]) - Constructor for class org.apache.commons.math4.legacy.genetics.BinaryChromosome: Constructor.
BinaryChromosome(List<Integer>) - Constructor for class org.apache.commons.math4.legacy.genetics.BinaryChromosome: Constructor.
BinaryMutation - Class in org.apache.commons.math4.legacy.genetics: Mutation for BinaryChromosomes.
BinaryMutation() - Constructor for class org.apache.commons.math4.legacy.genetics.BinaryMutation
BINOMIAL_INVALID_PARAMETERS_ORDER - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
BINOMIAL_NEGATIVE_PARAMETER - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
BinomialConfidenceInterval - Interface in org.apache.commons.math4.legacy.stat.interval: Interface to generate confidence intervals for a binomial proportion.
binomialTest(int, int, double, AlternativeHypothesis) - Method in class org.apache.commons.math4.legacy.stat.inference.BinomialTest: Returns the observed significance level, or p-value, associated with a Binomial test.
binomialTest(int, int, double, AlternativeHypothesis, double) - Method in class org.apache.commons.math4.legacy.stat.inference.BinomialTest: Returns whether the null hypothesis can be rejected with the given confidence level.
BinomialTest - Class in org.apache.commons.math4.legacy.stat.inference: Implements binomial test statistics.
BinomialTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.BinomialTest
BisectionSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements the bisection algorithm for finding zeros of univariate real functions.
BisectionSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BisectionSolver: Construct a solver with default accuracy (1e-6).
BisectionSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BisectionSolver: Construct a solver.
BisectionSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BisectionSolver: Construct a solver.
BivariateFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a bivariate real function.
BivariateGridInterpolator - Interface in org.apache.commons.math4.legacy.analysis.interpolation: Interface representing a bivariate real interpolating function where the sample points must be specified on a regular grid.
BLAND - org.apache.commons.math4.legacy.optim.linear.PivotSelectionRule: The first variable with a negative coefficient in the objective function row will be chosen as entering variable.
BLOCK_SIZE - Static variable in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Block size.
BLOCK_SIZE - Static variable in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Block size.
BlockFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Cache-friendly implementation of FieldMatrix using a flat arrays to store square blocks of the matrix.
BlockFieldMatrix(int, int, T[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a new dense matrix copying entries from block layout data.
BlockFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a new matrix with the supplied row and column dimensions.
BlockFieldMatrix(T[][]) - Constructor for class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a new dense matrix copying entries from raw layout data.
blockInverse(RealMatrix, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Computes the inverse of the given matrix by splitting it into 4 sub-matrices.
BlockRealMatrix - Class in org.apache.commons.math4.legacy.linear: Cache-friendly implementation of RealMatrix using a flat arrays to store square blocks of the matrix.
BlockRealMatrix(double[][]) - Constructor for class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a new dense matrix copying entries from raw layout data.
BlockRealMatrix(int, int) - Constructor for class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a new matrix with the supplied row and column dimensions.
BlockRealMatrix(int, int, double[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a new dense matrix copying entries from block layout data.
BOBYQA_BOUND_DIFFERENCE_CONDITION - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
BOBYQAOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: Powell's BOBYQA algorithm.
BOBYQAOptimizer(int) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer
BOBYQAOptimizer(int, double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer
bootstrap(double[], double[], int, boolean, UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Estimates the p-value of a two-sample Kolmogorov-Smirnov test evaluating the null hypothesis that x and y are samples drawn from the same probability distribution.
BOTH - org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Include both the first and last points.
boundedToUnbounded(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter: Maps an array from bounded to unbounded.
bracket(UnivariateFunction, double, double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0 and maximumIterations set to Integer.MAX_VALUE.
bracket(UnivariateFunction, double, double, double, double, double, int) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: This method attempts to find two values a and b satisfying lowerBound <= a < initial < b <= upperBound f(a) * f(b) <= 0 If f is continuous on [a,b], this means that a and b bracket a root of f.
bracket(UnivariateFunction, double, double, double, int) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0.
BracketedRealFieldUnivariateSolver<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (univariate real) root-finding algorithms that maintain a bracketed solution.
BracketedUnivariateSolver<FUNC extends UnivariateFunction> - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (univariate real) root-finding algorithms that maintain a bracketed solution.
BracketFinder - Class in org.apache.commons.math4.legacy.optim.univariate: Provide an interval that brackets a local optimum of a function.
BracketFinder() - Constructor for class org.apache.commons.math4.legacy.optim.univariate.BracketFinder: Constructor with default values 100, 500 (see the other constructor).
BracketFinder(double, int) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.BracketFinder: Create a bracketing interval finder.
BracketingNthOrderBrentSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: This class implements a modification of the Brent algorithm.
BracketingNthOrderBrentSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Construct a solver with default accuracy and maximal order (1e-6 and 5 respectively).
BracketingNthOrderBrentSolver(double, double, double, int) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Construct a solver.
BracketingNthOrderBrentSolver(double, double, int) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Construct a solver.
BracketingNthOrderBrentSolver(double, int) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Construct a solver.
BrentOptimizer - Class in org.apache.commons.math4.legacy.optim.univariate: For a function defined on some interval (lo, hi), this class finds an approximation x to the point at which the function attains its minimum.
BrentOptimizer(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.BrentOptimizer: The arguments are used for implementing the original stopping criterion of Brent's algorithm.
BrentOptimizer(double, double, ConvergenceChecker<UnivariatePointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.BrentOptimizer: The arguments are used implement the original stopping criterion of Brent's algorithm.
BrentSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: This class implements the Brent algorithm for finding zeros of real univariate functions.
BrentSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Construct a solver with default absolute accuracy (1e-6).
BrentSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Construct a solver.
BrentSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Construct a solver.
BrentSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Construct a solver.
build() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Construct a LeastSquaresProblem from the data in this builder.
buildArray(Field<T>, int) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Build an array of elements.
buildArray(Field<T>, int, int) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Build a double dimension array of elements.

C

calculateAdjustedRSquared() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Returns the adjusted R-squared statistic, defined by the formula R²_adj = 1 - [SSR (n - 1)] / [SSTO (n - p)] where SSR is the sum of squared residuals, SSTO is the total sum of squares, n is the number of observations and p is the number of parameters estimated (including the intercept).
calculateBeta() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the beta of multiple linear regression in matrix notation.
calculateBeta() - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Calculates beta by GLS.
calculateBeta() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Calculates the regression coefficients using OLS.
calculateBetaVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the beta variance of multiple linear regression in matrix notation.
calculateBetaVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Calculates the variance on the beta.
calculateBetaVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Calculates the variance-covariance matrix of the regression parameters.
calculateErrorVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the variance of the error term.
calculateErrorVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Calculates the estimated variance of the error term using the formula
calculateHat() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Compute the "hat" matrix.
calculateResiduals() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the residuals of multiple linear regression in matrix notation.
calculateResidualSumOfSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Returns the sum of squared residuals.
calculateRSquared() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Returns the R-Squared statistic, defined by the formula R² = 1 - SSR / SSTO where SSR is the sum of squared residuals and SSTO is the total sum of squares
calculateTotalSumOfSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Returns the sum of squared deviations of Y from its mean.
calculateYVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the variance of the y values.
CalinskiHarabasz - Class in org.apache.commons.math4.legacy.ml.clustering.evaluation: Compute the Calinski and Harabasz score.
CalinskiHarabasz() - Constructor for class org.apache.commons.math4.legacy.ml.clustering.evaluation.CalinskiHarabasz
canAdd(AnyMatrix) - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Checks that this matrix and the other matrix can be added.
CanberraDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the Canberra distance between two points.
CanberraDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.CanberraDistance
canIncrement() - Method in class org.apache.commons.math4.legacy.core.IntegerSequence.Incrementor: Checks whether incrementing the counter nTimes is allowed.
canIncrement(int) - Method in class org.apache.commons.math4.legacy.core.IntegerSequence.Incrementor: Checks whether incrementing the counter several times is allowed.
canMultiply(AnyMatrix) - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Checks that this matrix can be multiplied by the other matrix.
CANNOT_CLEAR_STATISTIC_CONSTRUCTED_FROM_EXTERNAL_MOMENTS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_COMPUTE_0TH_ROOT_OF_UNITY - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_COMPUTE_BETA_DENSITY_AT_0_FOR_SOME_ALPHA - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_COMPUTE_BETA_DENSITY_AT_1_FOR_SOME_BETA - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_COMPUTE_NTH_ROOT_FOR_NEGATIVE_N - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_DISCARD_NEGATIVE_NUMBER_OF_ELEMENTS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_FORMAT_INSTANCE_AS_3D_VECTOR - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_FORMAT_INSTANCE_AS_COMPLEX - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_FORMAT_INSTANCE_AS_REAL_VECTOR - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_FORMAT_OBJECT_TO_FRACTION - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_INCREMENT_STATISTIC_CONSTRUCTED_FROM_EXTERNAL_MOMENTS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_NORMALIZE_A_ZERO_NORM_VECTOR - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_PARSE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_PARSE_AS_TYPE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_RETRIEVE_AT_NEGATIVE_INDEX - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_SET_AT_NEGATIVE_INDEX - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_SUBSTITUTE_ELEMENT_FROM_EMPTY_ARRAY - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CANNOT_TRANSFORM_TO_DOUBLE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CARDAN_ANGLES_SINGULARITY - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
cbrt() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Cubic root.
cbrt() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Cubic root.
cbrt() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Cubic root.
cbrt() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Cubic root.
cbrt(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Compute the cubic root of a number.
cbrt(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
Cbrt - Class in org.apache.commons.math4.legacy.analysis.function: Cube root function.
Cbrt() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Cbrt
cdf(double, int) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Calculates \(P(D_n < d)\) using the method described in [1] with quick decisions for extreme values given in [2] (see above).
cdf(double, int, boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Calculates P(D_n < d) using method described in [1] with quick decisions for extreme values given in [2] (see above).
cdfExact(double, int) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Calculates P(D_n < d).
ceil() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get the smallest whole number larger than instance.
ceil() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Get the smallest whole number larger than instance.
ceil() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Round to an integer using the round ceil mode.
ceil() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Get the smallest whole number larger than instance.
ceil(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Get the smallest whole number larger than x.
ceil(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
Ceil - Class in org.apache.commons.math4.legacy.analysis.function: ceil function.
Ceil() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Ceil
CENTER - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.HorizontalDirection: Current column.
CENTER - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.VerticalDirection: Current row.
CentralPivotingStrategy - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: A mid point strategy based on the average of begin and end indices.
CentralPivotingStrategy() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.CentralPivotingStrategy
centroid() - Method in class org.apache.commons.math4.legacy.ml.clustering.Cluster: Computes the centroid of the cluster.
CentroidCluster<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: A Cluster used by centroid-based clustering algorithms.
CentroidCluster(Clusterable) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.CentroidCluster: Build a cluster centered at a specified point.
ChebyshevDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the L_∞ (max of abs) distance between two points.
ChebyshevDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.ChebyshevDistance
check(double) - Static method in exception org.apache.commons.math4.legacy.exception.NotFiniteNumberException: Check that the argument is a real number.
check(double[]) - Static method in exception org.apache.commons.math4.legacy.exception.NotFiniteNumberException: Check that all the elements are real numbers.
check(Object) - Static method in exception org.apache.commons.math4.legacy.exception.NullArgumentException: Checks that an object is not null.
check(Object, Localizable, Object...) - Static method in exception org.apache.commons.math4.legacy.exception.NullArgumentException: Checks that an object is not null.
checkAdd(AnyMatrix) - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Checks that this matrix and the other matrix can be added.
checkAdditionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if matrices are addition compatible.
checkColumnIndex(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Check if a column index is valid.
checkColumnIndex(AnyMatrix, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if a column index is valid.
checkCompatibility(DSCompiler) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Check rules set compatibility.
checkEqualLength(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that both arrays have the same length.
checkEqualLength(double[], double[], boolean) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that both arrays have the same length.
checkEqualLength(int[], int[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that both arrays have the same length.
checkEqualLength(int[], int[], boolean) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that both arrays have the same length.
checker(ConvergenceChecker<LeastSquaresProblem.Evaluation>) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the convergence checker.
checkerPair(ConvergenceChecker<PointVectorValuePair>) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the convergence checker.
checkIndex(int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Check if an index is valid.
checkIndices(int, int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Checks that the indices of a subvector are valid.
checkMatrixIndex(AnyMatrix, int, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if matrix indices are valid.
checkMultiplicationCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if matrices are multiplication compatible.
checkMultiply(AnyMatrix) - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Checks that this matrix can be multiplied by the other matrix.
checkNonNegative(long[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that all entries of the input array are >= 0.
checkNonNegative(long[][]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check all entries of the input array are >= 0.
checkNotNaN(double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that no entry of the input array is NaN.
checkOrder(double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that the given array is sorted in strictly increasing order.
checkOrder(double[], MathArrays.OrderDirection, boolean) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that the given array is sorted.
checkOrder(double[], MathArrays.OrderDirection, boolean, boolean) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that the given array is sorted.
checkParameters(RealLinearOperator, RealLinearOperator, RealVector, RealVector) - Static method in class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Performs all dimension checks on the parameters of solve and solveInPlace, and throws an exception if one of the checks fails.
checkParameters(RealLinearOperator, RealVector, RealVector) - Static method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolver: Performs all dimension checks on the parameters of solve and solveInPlace, and throws an exception if one of the checks fails.
checkPositive(double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Check that all entries of the input array are strictly positive.
checkRectangular(long[][]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Throws DimensionMismatchException if the input array is not rectangular.
checkRowIndex(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Check if a row index is valid.
checkRowIndex(AnyMatrix, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if a row index is valid.
checkSubMatrixIndex(int[], int[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Check if submatrix ranges indices are valid.
checkSubMatrixIndex(int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Check if submatrix ranges indices are valid.
checkSubMatrixIndex(AnyMatrix, int[], int[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if submatrix ranges indices are valid.
checkSubMatrixIndex(AnyMatrix, int, int, int, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if submatrix ranges indices are valid.
checkSubtractionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if matrices are subtraction compatible.
checkSymmetric(RealMatrix, double) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Checks whether a matrix is symmetric.
checkValidity(List<Double>) - Method in class org.apache.commons.math4.legacy.genetics.RandomKey: Asserts that representation can represent a valid chromosome.
checkValidity(List<Integer>) - Method in class org.apache.commons.math4.legacy.genetics.BinaryChromosome: Asserts that representation can represent a valid chromosome.
checkValidity(List<T>) - Method in class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Asserts that representation can represent a valid chromosome.
checkVectorDimensions(int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Check if instance dimension is equal to some expected value.
checkVectorDimensions(int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Check if instance dimension is equal to some expected value.
checkVectorDimensions(int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Check if instance dimension is equal to some expected value.
checkVectorDimensions(int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Check if instance dimension is equal to some expected value.
checkVectorDimensions(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Check if instance and specified vectors have the same dimension.
checkVectorDimensions(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Check if instance and specified vectors have the same dimension.
checkVectorDimensions(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Check if instance and specified vectors have the same dimension.
chiSquare(double[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Computes the Chi-Square statistic comparing observed and expected frequency counts.
chiSquare(double[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquare(long[][]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Computes the Chi-Square statistic associated with a chi-square test of independence based on the input counts array, viewed as a two-way table.
chiSquare(long[][]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Computes a Chi-Square two sample test statistic comparing bin frequency counts in observed1 and observed2.
chiSquareDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTest(double[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the observed frequency counts to those in the expected array.
chiSquareTest(double[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTest(double[], long[], double) - Method in class org.apache.commons.math4.legacy.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(double[], long[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTest(long[][]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input counts array, viewed as a two-way table.
chiSquareTest(long[][]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTest(long[][], double) - Method in class org.apache.commons.math4.legacy.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(long[][], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
ChiSquareTest - Class in org.apache.commons.math4.legacy.stat.inference: Implements Chi-Square test statistics.
ChiSquareTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Construct a ChiSquareTest.
chiSquareTestDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: 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[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTestDataSetsComparison(long[], long[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Performs a Chi-Square two sample test comparing two binned data sets.
chiSquareTestDataSetsComparison(long[], long[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
CHOLESKY - org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition: Solve by forming the normal equations (J^TJx=J^Tr) and using the CholeskyDecomposition.
CholeskyDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the Cholesky decomposition of a matrix.
CholeskyDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Calculates the Cholesky decomposition of the given matrix.
CholeskyDecomposition(RealMatrix, double, double) - Constructor for class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Calculates the Cholesky decomposition of the given matrix.
Chromosome - Class in org.apache.commons.math4.legacy.genetics: Individual in a population.
Chromosome() - Constructor for class org.apache.commons.math4.legacy.genetics.Chromosome
ChromosomePair - Class in org.apache.commons.math4.legacy.genetics: A pair of Chromosome objects.
ChromosomePair(Chromosome, Chromosome) - Constructor for class org.apache.commons.math4.legacy.genetics.ChromosomePair: Create a chromosome pair.
ClampedSplineInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Computes a clamped cubic spline interpolation for the data set.
ClampedSplineInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.ClampedSplineInterpolator
CLASS_DOESNT_IMPLEMENT_COMPARABLE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ClassicalRungeKuttaFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.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).
ClassicalRungeKuttaFieldIntegrator(Field<T>, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Simple constructor.
ClassicalRungeKuttaIntegrator - Class in org.apache.commons.math4.legacy.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.math4.legacy.ode.nonstiff.ClassicalRungeKuttaIntegrator: Simple constructor.
classify() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Returns the type - one of FINITE, INFINITE, SNAN, QNAN.
clear() - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Removes all observations from this container.
clear() - Method in class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Method that will called in order to clear all stored optima.
clear() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultiStartMultivariateOptimizer: Method that will called in order to clear all stored optima.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Clears the internal state of the Statistic.
clear() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Clears the frequency table.
clear() - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: As the name suggests, clear wipes the internals and reorders everything in the canonical order.
clear() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Clears all data from the model.
clear() - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Clears internal buffers and resets the regression model.
clearEventHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Remove all the event handlers that have been added to the integrator.
clearEventHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Remove all the event handlers that have been added to the integrator.
clearEventHandlers() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Remove all the event handlers that have been added to the integrator.
clearEventHandlers() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Remove all the event handlers that have been added to the integrator.
clearIEEEFlags() - Method in class org.apache.commons.math4.legacy.core.dfp.DfpField: Clears the IEEE 854 status flags.
clearStepHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Remove all the step handlers that have been added to the integrator.
clearStepHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Remove all the step handlers that have been added to the integrator.
clearStepHandlers() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Remove all the step handlers that have been added to the integrator.
clearStepHandlers() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Remove all the step handlers that have been added to the integrator.
ClopperPearsonInterval - Class in org.apache.commons.math4.legacy.stat.interval: Implements the Clopper-Pearson method for creating a binomial proportion confidence interval.
ClopperPearsonInterval() - Constructor for class org.apache.commons.math4.legacy.stat.interval.ClopperPearsonInterval
CLOSE_VERTICES - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CLOSEST_ORTHOGONAL_MATRIX_HAS_NEGATIVE_DETERMINANT - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.Clusterer: Perform a cluster analysis on the given set of Clusterable instances.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.DBSCANClusterer: Performs DBSCAN cluster analysis.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.ElkanKMeansPlusPlusClusterer: Runs the K-means++ clustering algorithm.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Performs Fuzzy K-Means cluster analysis.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Runs the K-means++ clustering algorithm.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.MiniBatchKMeansClusterer: Runs the MiniBatch K-means clustering algorithm.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.MultiKMeansPlusPlusClusterer: Runs the K-means++ clustering algorithm.
Cluster<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Cluster holding a set of Clusterable points.
Cluster() - Constructor for class org.apache.commons.math4.legacy.ml.clustering.Cluster: Build a cluster centered at a specified point.
Clusterable - Interface in org.apache.commons.math4.legacy.ml.clustering: Interface for n-dimensional points that can be clustered together.
Clusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Base class for clustering algorithms.
Clusterer(DistanceMeasure) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.Clusterer: Build a new clusterer with the given DistanceMeasure.
ClusterEvaluator - Interface in org.apache.commons.math4.legacy.ml.clustering: Defines a measure of the quality of clusters.
ClusterRanking - Interface in org.apache.commons.math4.legacy.ml.clustering: Evaluates the quality of a set of clusters.
CM - org.apache.commons.math4.core.jdkmath.JdkMath.Impl: Commons Math.
CMAESOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: An implementation of the active Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for non-linear, non-convex, non-smooth, global function minimization.
CMAESOptimizer(int, double, boolean, int, int, UniformRandomProvider, boolean, ConvergenceChecker<PointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer
collector(BivariateFunction, double) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Returns a MultivariateFunction h(x[]).
collector(BivariateFunction, UnivariateFunction, double) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Returns a MultivariateFunction h(x[]).
COLUMN_INDEX - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
COLUMN_INDEX_OUT_OF_RANGE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
combine(double, double, RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns a new vector representing a * this + b * y, the linear combination of this and y.
combine(double, double, RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns a new vector representing a * this + b * y, the linear combination of this and y.
combine(BivariateFunction, UnivariateFunction, UnivariateFunction) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Returns the univariate function h(x) = combiner(f(x), g(x)).
combineToSelf(double, double, RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Updates this with the linear combination of this and y.
combineToSelf(double, double, RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Updates this with the linear combination of this and y.
comparatorPermutation(List<S>, Comparator<S>) - Static method in class org.apache.commons.math4.legacy.genetics.RandomKey: Generates a representation of a permutation corresponding to the data sorted by comparator.
compareAndSetFeatures(double[], double[]) - Method in class org.apache.commons.math4.neuralnet.Neuron: Tries to atomically update the neuron's features.
compareTo(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.Chromosome: Compares two chromosomes based on their fitness.
compareTo(BigReal) - Method in class org.apache.commons.math4.legacy.linear.BigReal
complainIfNotSupported(String) - Method in class org.apache.commons.math4.legacy.ode.AbstractParameterizable: Check if a parameter is supported and throw an IllegalArgumentException if not.
complement(int) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Negate the mantissa of this by computing the complement.
ComplexFormat - Class in org.apache.commons.math4.legacy.util: Formats a Complex number in cartesian format "Re(c) + Im(c)i".
ComplexFormat() - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with the default imaginary character, 'i', and the default number format for both real and imaginary parts.
ComplexFormat(String) - Constructor for class org.apache.commons.math4.legacy.util.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.math4.legacy.util.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.math4.legacy.util.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.
ComplexFormat(NumberFormat) - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with a custom number format for both real and imaginary parts.
ComplexFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with a custom number format for the real part and a custom number format for the imaginary part.
ComplexTransform - Interface in org.apache.commons.math4.transform: Complex transform.
compose(double...) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Compute composition of the instance by a univariate function.
compose(double[], int, double[], double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute composition of a derivative structure by a function.
compose(double, double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Compute composition of the instance by a univariate function.
compose(UnivariateDifferentiableFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Composes functions.
compose(UnivariateFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Composes functions.
CompositeFormat - Class in org.apache.commons.math4.legacy.util: Base class for formatters of composite objects (complex numbers, vectors ...).
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.CanberraDistance: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.ChebyshevDistance: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in interface org.apache.commons.math4.legacy.ml.distance.DistanceMeasure: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.EarthMoversDistance: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.EuclideanDistance: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.ManhattanDistance: Compute the distance between two n-dimensional vectors.
compute(List<? extends Cluster<? extends Clusterable>>) - Method in interface org.apache.commons.math4.legacy.ml.clustering.ClusterRanking: Computes the rank (higher is better).
computeCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Calculate the coefficients of Lagrange polynomial from the interpolation data.
computeCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Calculate the normal polynomial coefficients given the Newton form.
computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Computes the Kendall's Tau rank correlation matrix for the columns of the input rectangular array.
computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Computes the correlation matrix for the columns of the input rectangular array.
computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Computes the Spearman's rank correlation matrix for the columns of the input rectangular array.
computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Computes the Kendall's Tau rank correlation matrix for the columns of the input matrix.
computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Computes the correlation matrix for the columns of the input matrix, using PearsonsCorrelation.correlation(double[], double[]).
computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Computes the Spearman's rank correlation matrix for the columns of the input matrix.
computeCovarianceMatrix(double[][]) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a covariance matrix from a rectangular array whose columns represent covariates.
computeCovarianceMatrix(double[][], boolean) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Compute a covariance matrix from a rectangular array whose columns represent covariates.
computeCovarianceMatrix(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a covariance matrix from a matrix whose columns represent covariates.
computeCovarianceMatrix(RealMatrix, boolean) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Compute a covariance matrix from a matrix whose columns represent covariates.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Compute the derivatives and check the number of evaluations.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get the current time derivative of the complete state vector.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.FirstOrderConverter: Get the current time derivative of the state vector.
computeDerivatives(double, double[], double[]) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderDifferentialEquations: Get the current time derivative of the state vector.
computeDerivatives(double, double[], double[], double[], double[]) - Method in interface org.apache.commons.math4.legacy.ode.SecondaryEquations: Compute the derivatives related to the secondary state parameters.
computeDerivatives(T, T[]) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Compute the derivatives and check the number of evaluations.
computeDerivatives(T, T[]) - Method in class org.apache.commons.math4.legacy.ode.FieldExpandableODE: Get the current time derivative of the complete state vector.
computeDerivatives(T, T[]) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldDifferentialEquations: Get the current time derivative of the state vector.
computeDerivatives(T, T[], T[], T[]) - Method in interface org.apache.commons.math4.legacy.ode.FieldSecondaryEquations: Compute the derivatives related to the secondary state parameters.
computeDividedDifference(double[], double[]) - Static method in class org.apache.commons.math4.legacy.analysis.interpolation.DividedDifferenceInterpolator: Return a copy of the divided difference array.
computeExp(Dfp, Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpField: Compute exp(a).
computeImage(NeuronSquareMesh2D) - Method in interface org.apache.commons.math4.neuralnet.twod.util.MapVisualization: Creates an image of the map.
computeImage(NeuronSquareMesh2D) - Method in class org.apache.commons.math4.neuralnet.twod.util.UnifiedDistanceMatrix: Computes the distances between a unit of the map and its neighbours.
computeImage(NeuronSquareMesh2D, Iterable<double[]>) - Method in interface org.apache.commons.math4.neuralnet.twod.util.MapDataVisualization: Creates an image of the data metrics when represented by the map.
computeImage(NeuronSquareMesh2D, Iterable<double[]>) - Method in class org.apache.commons.math4.neuralnet.twod.util.SmoothedDataHistogram: Creates an image of the data metrics when represented by the map.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(FieldEquationsMapper<T>, T, T, T, T) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Compute the state and derivatives at the interpolated time.
computeJacobian(double[]) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.ValueAndJacobianFunction: Compute the Jacobian.
computeLn(Dfp, Dfp, Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpField: Compute ln(a).
computeMainStateJacobian(double, double[], double[], double[][]) - Method in interface org.apache.commons.math4.legacy.ode.MainStateJacobianProvider: Compute the jacobian matrix of ODE with respect to main state.
computeObjectiveGradient(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.GradientMultivariateOptimizer: Compute the gradient vector.
computeObjectiveValue(double) - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Compute the objective function value.
computeObjectiveValue(double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Compute the objective function value.
computeObjectiveValue(double) - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer: Computes the objective function value.
computeObjectiveValue(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer: Computes the objective function value.
computeObjectiveValueAndDerivative(double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateDifferentiableSolver: Compute the objective function value.
computeParameterJacobian(double, double[], double[], String, double[]) - Method in interface org.apache.commons.math4.legacy.ode.ParameterJacobianProvider: Compute the Jacobian matrix of ODE with respect to one parameter.
computeQualityIndicators(Iterable<double[]>) - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Computes various indicators of the quality of the representation of the given data by this map.
computeQuantizationError(Iterable<double[]>, Iterable<Neuron>, DistanceMeasure) - Static method in class org.apache.commons.math4.neuralnet.MapUtils: Computes the quantization error.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.BaseRuleFactory: Computes the rule for the given order.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.HermiteRuleFactory: Computes the rule for the given order.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.LaguerreRuleFactory: Computes the rule for the given order.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.LegendreHighPrecisionRuleFactory: Computes the rule for the given order.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.LegendreRuleFactory: Computes the rule for the given order.
computeSecondDerivatives(double, double[], double[], double[]) - Method in interface org.apache.commons.math4.legacy.ode.SecondOrderDifferentialEquations: Get the current time derivative of the state vector.
computeStepGrowShrinkFactor(double) - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Compute step grow/shrink factor according to normalized error.
computeStepGrowShrinkFactor(T) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Compute step grow/shrink factor according to normalized error.
computeTopographicError(Iterable<double[]>, Network, DistanceMeasure) - Static method in class org.apache.commons.math4.neuralnet.MapUtils: Computes the topographic error.
computeValue(double[]) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.ValueAndJacobianFunction: Compute the value.
concatenate(double[]...) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Concatenates a sequence of arrays.
ConfidenceInterval - Class in org.apache.commons.math4.legacy.stat.interval: Represents an interval estimate of a population parameter.
ConfidenceInterval(double, double, double) - Constructor for class org.apache.commons.math4.legacy.stat.interval.ConfidenceInterval: Create a confidence interval with the given bounds and confidence level.
ConjugateGradient - Class in org.apache.commons.math4.legacy.linear: This is an implementation of the conjugate gradient method for RealLinearOperator.
ConjugateGradient(int, double, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ConjugateGradient: Creates a new instance of this class, with default stopping criterion.
ConjugateGradient(IterationManager, double, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ConjugateGradient: Creates a new instance of this class, with default stopping criterion and custom iteration manager.
Constant - Class in org.apache.commons.math4.legacy.analysis.function: Constant function.
Constant(double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Constant
CONSTRAINT - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CONTINUE - org.apache.commons.math4.legacy.ode.events.Action: Continue indicator.
CONTINUE - org.apache.commons.math4.legacy.ode.events.EventHandler.Action: Continue indicator.
CONTINUED_FRACTION_INFINITY_DIVERGENCE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CONTINUED_FRACTION_NAN_DIVERGENCE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ContinuousOutputFieldModel<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.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.
ContinuousOutputFieldModel() - Constructor for class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Simple constructor.
ContinuousOutputModel - Class in org.apache.commons.math4.legacy.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.math4.legacy.ode.ContinuousOutputModel: Simple constructor.
CONTRACTION_CRITERIA_SMALLER_THAN_EXPANSION_FACTOR - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CONTRACTION_CRITERIA_SMALLER_THAN_ONE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
converged(int, LeastSquaresProblem.Evaluation, LeastSquaresProblem.Evaluation) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.EvaluationRmsChecker: Check if the optimization algorithm has converged.
converged(int, PointValuePair, PointValuePair) - Method in class org.apache.commons.math4.legacy.optim.SimpleValueChecker: Check if the optimization algorithm has converged considering the last two points.
converged(int, PointVectorValuePair, PointVectorValuePair) - Method in class org.apache.commons.math4.legacy.optim.SimpleVectorValueChecker: Check if the optimization algorithm has converged considering the last two points.
converged(int, UnivariatePointValuePair, UnivariatePointValuePair) - Method in class org.apache.commons.math4.legacy.optim.univariate.SimpleUnivariateValueChecker: Check if the optimization algorithm has converged considering the last two points.
converged(int, PAIR, PAIR) - Method in class org.apache.commons.math4.legacy.optim.AbstractConvergenceChecker: Check if the optimization algorithm has converged.
converged(int, PAIR, PAIR) - Method in interface org.apache.commons.math4.legacy.optim.ConvergenceChecker: Check if the optimization algorithm has converged.
converged(int, PAIR, PAIR) - Method in class org.apache.commons.math4.legacy.optim.SimplePointChecker: Check if the optimization algorithm has converged considering the last two points.
CONVERGENCE_FAILED - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ConvergenceChecker<PAIR> - Interface in org.apache.commons.math4.legacy.optim: This interface specifies how to check if an optimization algorithm has converged.
ConvergenceException - Exception in org.apache.commons.math4.legacy.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.math4.legacy.exception.ConvergenceException: Construct the exception.
ConvergenceException(Localizable, Object...) - Constructor for exception org.apache.commons.math4.legacy.exception.ConvergenceException: Construct the exception with a specific context and arguments.
convolve(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Calculates the convolution between two sequences.
copy() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Perform a copy.
copy() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere2D: Perform a copy.
copy() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Copies this matrix.
copy() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Make a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Make a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns a (deep) copy of this vector.
copy() - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Make a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns a (deep) copy of this.
copy() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Make a (deep) copy of this.
copy() - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Returns a (deep) copy of this vector.
copy() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns a (deep) copy of this vector.
copy() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Make a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Copy the instance.
copy() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Copy the instance.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns a copy of this DescriptiveStatistics instance with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns a copy of the statistic with the same internal state.
copy() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns a copy of this SummaryStatistics instance with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns a copy of this SynchronizedDescriptiveStatistics instance with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns a copy of this SynchronizedSummaryStatistics instance with the same internal state.
copy() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.UnivariateStatistic: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.neuralnet.Network: Performs a deep copy of this instance.
copy() - Method in class org.apache.commons.math4.neuralnet.Neuron: Performs a deep copy of this instance.
copy() - Method in class org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D: Performs a deep copy of this instance.
copy(Field<T>, T[][]) - Method in class org.apache.commons.math4.legacy.ode.FieldODEState: Copy a two-dimensions array.
copy(DescriptiveStatistics, DescriptiveStatistics) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Copies source to dest.
copy(GeometricMean, GeometricMean) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Copies source to dest.
copy(Kurtosis, Kurtosis) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Copies source to dest.
copy(Mean, Mean) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Copies source to dest.
copy(SecondMoment, SecondMoment) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Copies source to dest.
copy(SemiVariance, SemiVariance) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Copies source to dest.
copy(Skewness, Skewness) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Copies source to dest.
copy(StandardDeviation, StandardDeviation) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Copies source to dest.
copy(Variance, Variance) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Copies source to dest.
copy(Max, Max) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Copies source to dest.
copy(Min, Min) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Copies source to dest.
copy(Product, Product) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Copies source to dest.
copy(SumOfLogs, SumOfLogs) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Copies source to dest.
copy(SumOfSquares, SumOfSquares) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Copies source to dest.
copy(Sum, Sum) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Copies source to dest.
copy(SummaryStatistics, SummaryStatistics) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Copies source to dest.
copy(SynchronizedDescriptiveStatistics, SynchronizedDescriptiveStatistics) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Copies source to dest.
copy(SynchronizedSummaryStatistics, SynchronizedSummaryStatistics) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Copies source to dest.
copySign(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Returns the instance with the sign of the argument.
copySign(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Returns the instance with the sign of the argument.
copySign(double) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Returns the instance with the sign of the argument.
copySign(double) - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Returns the instance with the sign of the argument.
copySign(double, double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Returns the first argument with the sign of the second argument.
copySign(double, double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
copySign(float, float) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Returns the first argument with the sign of the second argument.
copySign(float, float) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
copySign(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Returns the instance with the sign of the argument.
copySign(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Returns the instance with the sign of the argument.
copySign(Dfp) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Returns the instance with the sign of the argument.
copySign(Dfp, Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Creates an instance that is the same as x except that it has the sign of y.
copySign(T) - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Returns the instance with the sign of the argument.
copySubMatrix(int[], int[], double[][]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Copy a submatrix.
copySubMatrix(int[], int[], double[][]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Copy a submatrix.
copySubMatrix(int[], int[], T[][]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Copy a submatrix.
copySubMatrix(int[], int[], T[][]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Copy a submatrix.
copySubMatrix(int, int, int, int, double[][]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Copy a submatrix.
copySubMatrix(int, int, int, int, double[][]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Copy a submatrix.
copySubMatrix(int, int, int, int, T[][]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Copy a submatrix.
copySubMatrix(int, int, int, int, T[][]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Copy a submatrix.
correct(double[]) - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Correct the current state estimate with an actual measurement.
correct(RealVector) - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Correct the current state estimate with an actual measurement.
CorrelatedVectorFactory - Class in org.apache.commons.math4.legacy.random: Generates vectors with with correlated components.
CorrelatedVectorFactory(double[], RealMatrix, double) - Constructor for class org.apache.commons.math4.legacy.random.CorrelatedVectorFactory: Correlated vector factory.
CorrelatedVectorFactory(RealMatrix, double) - Constructor for class org.apache.commons.math4.legacy.random.CorrelatedVectorFactory: Null mean correlated vector factory.
correlation(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Computes the Kendall's Tau rank correlation coefficient between the two arrays.
correlation(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Computes the Pearson's product-moment correlation coefficient between two arrays.
correlation(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Computes the Spearman's rank correlation coefficient between the two arrays.
cos() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Cosine operation.
cos() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Cosine operation.
cos() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Cosine operation.
cos() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Cosine operation.
cos(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Cosine function.
cos(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
cos(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute cosine of a derivative structure.
cos(Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpMath: computes the cosine of the argument.
Cos - Class in org.apache.commons.math4.legacy.analysis.function: Cosine function.
Cos() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Cos
cosh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Hyperbolic cosine operation.
cosh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Hyperbolic cosine operation.
cosh() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Hyperbolic cosine operation.
cosh() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Hyperbolic cosine operation.
cosh(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Compute the hyperbolic cosine of a number.
cosh(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
cosh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute hyperbolic cosine of a derivative structure.
Cosh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic cosine function.
Cosh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Cosh
cosine(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Computes the cosine of the angle between this vector and the argument.
cosInternal(Dfp[]) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpMath: Computes cos(a) Used when 0 < a < pi/4.
countEvaluations(LeastSquaresProblem, IntegerSequence.Incrementor) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Count the evaluations of a particular problem.
covariance(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Computes the covariance between the two arrays, using the bias-corrected formula.
covariance(double[], double[], boolean) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Computes the covariance between the two arrays.
Covariance - Class in org.apache.commons.math4.legacy.stat.correlation: Computes covariances for pairs of arrays or columns of a matrix.
Covariance() - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a Covariance with no data.
Covariance(double[][]) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(double[][], boolean) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a covariance matrix from a matrix whose columns represent covariates.
Covariance(RealMatrix, boolean) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a covariance matrix from a matrix whose columns represent covariates.
COVARIANCE_MATRIX - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
covarianceToCorrelation(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Derives a correlation matrix from a covariance matrix.
create() - Static method in class org.apache.commons.math4.legacy.core.IntegerSequence.Incrementor: Factory method that creates a default instance.
create() - Static method in class org.apache.commons.math4.legacy.fitting.GaussianCurveFitter: Creates a default curve fitter.
create() - Static method in class org.apache.commons.math4.legacy.fitting.HarmonicCurveFitter: Creates a default curve fitter.
create(boolean, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Create a new instance.
create(int) - Static method in class org.apache.commons.math4.legacy.fitting.PolynomialCurveFitter: Creates a default curve fitter.
create(K, V) - Static method in class org.apache.commons.math4.legacy.core.Pair: Convenience factory method that calls the constructor.
create(MultivariateFunction, Comparator<PointValuePair>, DoublePredicate) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.HedarFukushimaTransform: Creates a simplex transformation.
create(MultivariateFunction, Comparator<PointValuePair>, DoublePredicate) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.MultiDirectionalTransform: Creates a simplex transformation.
create(MultivariateFunction, Comparator<PointValuePair>, DoublePredicate) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.NelderMeadTransform: Creates a simplex transformation.
create(MultivariateFunction, Comparator<PointValuePair>, DoublePredicate) - Method in interface org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex.TransformFactory: Creates a simplex transformation.
create(MultivariateVectorFunction, MultivariateMatrixFunction, double[], double[], RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Create a LeastSquaresProblem from the given elements.
create(ParametricUnivariateFunction, double[]) - Static method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter: Creates a curve fitter.
create(ParametricUnivariateFunction, SimpleCurveFitter.ParameterGuesser) - Static method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter: Creates a curve fitter.
create(MultivariateJacobianFunction, RealVector, RealVector, RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Create a LeastSquaresProblem from the given elements.
create(MultivariateJacobianFunction, RealVector, RealVector, RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int, boolean, ParameterValidator) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Create a LeastSquaresProblem from the given elements.
create(MultivariateJacobianFunction, RealVector, RealVector, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Create a LeastSquaresProblem from the given elements.
create(RealLinearOperator) - Static method in class org.apache.commons.math4.legacy.linear.JacobiPreconditioner: Creates a new instance of this class.
create(Field<T>, int, int) - Static method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Factory method.
createBlocksLayout(int, int) - Static method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a data array in blocks layout.
createBlocksLayout(Field<T>, int, int) - Static method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a data array in blocks layout.
createChebyshevPolynomial(int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Chebyshev polynomial of the first kind.
createColumnFieldMatrix(T[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a column FieldMatrix using the data from the input array.
createColumnRealMatrix(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a column RealMatrix using the data from the input array.
createConstant(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Create a constant compatible with instance order and number of parameters.
createConstant(double) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Factory method creating a constant.
createContributingStatistics() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Creates and returns a SummaryStatistics whose data will be aggregated with those of this AggregateSummaryStatistics.
createFieldDiagonalMatrix(T[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a diagonal matrix with specified elements.
createFieldIdentityMatrix(Field<T>, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns dimension x dimension identity matrix.
createFieldMatrix(Field<T>, int, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a FieldMatrix with specified dimensions.
createFieldMatrix(T[][]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a FieldMatrix whose entries are the values in the the input array.
createFieldVector(T[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a FieldVector using the data from the input array.
createHermitePolynomial(int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Hermite polynomial.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Create an interpolator.
createInterval(int, int, double) - Method in class org.apache.commons.math4.legacy.stat.interval.AgrestiCoullInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createInterval(int, int, double) - Method in interface org.apache.commons.math4.legacy.stat.interval.BinomialConfidenceInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createInterval(int, int, double) - Method in class org.apache.commons.math4.legacy.stat.interval.ClopperPearsonInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createInterval(int, int, double) - Method in class org.apache.commons.math4.legacy.stat.interval.NormalApproximationInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createInterval(int, int, double) - Method in class org.apache.commons.math4.legacy.stat.interval.WilsonScoreInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createJacobiPolynomial(int, int, int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Jacobi polynomial.
createLaguerrePolynomial(int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Laguerre polynomial.
createLegendrePolynomial(int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Legendre polynomial.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.linear.BlockFieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.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 class org.apache.commons.math4.legacy.linear.DiagonalMatrix: 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.math4.legacy.linear.FieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.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.math4.legacy.linear.SparseFieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createNeuron(double[]) - Method in class org.apache.commons.math4.neuralnet.Network: Creates a neuron and assigns it a unique identifier.
createRealDiagonalMatrix(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a diagonal matrix with the specified diagonal elements.
createRealIdentityMatrix(int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns dimension x dimension identity matrix.
createRealMatrix(double[][]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a RealMatrix whose entries are the values in the the input array.
createRealMatrix(int, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a RealMatrix with specified dimensions.
createRealMatrixWithDiagonal(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a dense matrix with the specified diagonal elements.
createRealVector(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a RealVector using the data from the input array.
createRowFieldMatrix(T[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Create a row FieldMatrix using the data from the input array.
createRowRealMatrix(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Create a row RealMatrix using the data from the input array.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedDistribution: Creates a EnumeratedDistribution.Sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: Refer to EnumeratedDistribution.Sampler for implementation details.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution: Creates a sampler.
createVariable(int, double) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Factory method creating an independent variable.
CROSSING_BOUNDARY_LOOPS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
crossover(Chromosome, Chromosome) - Method in interface org.apache.commons.math4.legacy.genetics.CrossoverPolicy: Perform a crossover operation on the given chromosomes.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.CycleCrossover: Perform a crossover operation on the given chromosomes.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.NPointCrossover: Performs a N-point crossover.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.OnePointCrossover: Performs one point crossover.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.OrderedCrossover: Perform a crossover operation on the given chromosomes.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.UniformCrossover: Perform a crossover operation on the given chromosomes.
CROSSOVER_RATE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
CrossoverPolicy - Interface in org.apache.commons.math4.legacy.genetics: Policy used to create a pair of new chromosomes by performing a crossover operation on a source pair of chromosomes.
CUMULATIVE_PROBABILITY_RETURNED_NAN - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
cumulativeProbability(double) - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Algorithm description: Find the bin B that x belongs to. Compute P(B) = the mass of B and P(B-) = the combined mass of the bins below B. Compute K(B) = the probability mass of B with respect to the within-bin kernel and K(B-) = the kernel distribution evaluated at the lower endpoint of B Return P(B-) + P(B) * [K(x) - K(B-)] / K(B) where K(x) is the within-bin kernel distribution function evaluated at x. If K is a constant distribution, we return P(B-) + P(B) (counting the full mass of B).
cumulativeProbability(double) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution
cumulativeProbability(int) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution
currentState - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: current state.
CycleCrossover<T> - Class in org.apache.commons.math4.legacy.genetics: Cycle Crossover [CX] builds offspring from ordered chromosomes by identifying cycles between two parent chromosomes.
CycleCrossover() - Constructor for class org.apache.commons.math4.legacy.genetics.CycleCrossover: Creates a new CycleCrossover policy.
CycleCrossover(boolean) - Constructor for class org.apache.commons.math4.legacy.genetics.CycleCrossover: Creates a new CycleCrossover policy using the given randomStart behavior.

D

DANTZIG - org.apache.commons.math4.legacy.optim.linear.PivotSelectionRule: The classical rule, the variable with the most negative coefficient in the objective function row will be chosen as entering variable.
DBSCANClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: DBSCAN (density-based spatial clustering of applications with noise) algorithm.
DBSCANClusterer(double, int) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.DBSCANClusterer: Creates a new instance of a DBSCANClusterer.
DBSCANClusterer(double, int, DistanceMeasure) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.DBSCANClusterer: Creates a new instance of a DBSCANClusterer.
decode(List<T>) - Method in interface org.apache.commons.math4.legacy.genetics.PermutationChromosome: Permutes the sequence of objects of type T according to the permutation this chromosome represents.
decode(List<T>) - Method in class org.apache.commons.math4.legacy.genetics.RandomKey: Permutes the sequence of objects of type T according to the permutation this chromosome represents.
decompose(double[][]) - Method in class org.apache.commons.math4.legacy.linear.QRDecomposition: Decompose matrix.
decompose(double[][]) - Method in class org.apache.commons.math4.legacy.linear.RRQRDecomposition: Decompose matrix.
DecompositionSolver - Interface in org.apache.commons.math4.legacy.linear: Interface handling decomposition algorithms that can solve A × X = B.
DECREASING - org.apache.commons.math4.legacy.core.MathArrays.OrderDirection: Constant for decreasing direction.
decreasingExponential(double) - Static method in interface org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing.CoolingSchedule: Power-law cooling scheme: \[ T_i = T_0 * f^i \], where \( i \) is the current iteration.
decrementExact(int) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Decrement a number, detecting overflows.
decrementExact(int) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
decrementExact(long) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Decrement a number, detecting overflows.
decrementExact(long) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
DEFAULT_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Default absolute accuracy.
DEFAULT_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Default absolute accuracy.
DEFAULT_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.solvers.SecantSolver: Default absolute accuracy.
DEFAULT_ABSOLUTE_POSITIVITY_THRESHOLD - Static variable in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Default threshold below which diagonal elements are considered null and matrix not positive definite.
DEFAULT_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Default value for accuracy.
DEFAULT_BANDWIDTH - Static variable in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Default value of the bandwidth parameter.
DEFAULT_EXTEND - Static variable in class org.apache.commons.math4.legacy.analysis.interpolation.UnivariatePeriodicInterpolator: Default number of extension points of the samples array.
DEFAULT_FORMAT - Static variable in class org.apache.commons.math4.legacy.linear.MatrixUtils: The default format for RealMatrix objects.
DEFAULT_INITIAL_RADIUS - Static variable in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer: Default value for BOBYQAOptimizer.initialTrustRegionRadius: 10.0.
DEFAULT_MAX_ITERATIONS_COUNT - Static variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Default maximal iteration count.
DEFAULT_MIN_ITERATIONS_COUNT - Static variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Default minimal iteration count.
DEFAULT_NAN_STRATEGY - Static variable in class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: default NaN strategy.
DEFAULT_RELATIVE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Default relative accuracy.
DEFAULT_RELATIVE_SYMMETRY_THRESHOLD - Static variable in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Default threshold above which off-diagonal elements are considered too different and matrix not symmetric.
DEFAULT_ROBUSTNESS_ITERS - Static variable in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Default value of the number of robustness iterations.
DEFAULT_STOPPING_RADIUS - Static variable in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer: Default value for BOBYQAOptimizer.stoppingTrustRegionRadius: 1.0E-8.
DEFAULT_TIES_STRATEGY - Static variable in class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: default ties strategy.
DEFAULT_ZERO_TOLERANCE - Static variable in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Default Tolerance for having a value considered zero.
DefaultFieldMatrixChangingVisitor<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Default implementation of the FieldMatrixChangingVisitor interface.
DefaultFieldMatrixChangingVisitor(T) - Constructor for class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixChangingVisitor: Build a new instance.
DefaultFieldMatrixPreservingVisitor<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Default implementation of the FieldMatrixPreservingVisitor interface.
DefaultFieldMatrixPreservingVisitor(T) - Constructor for class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixPreservingVisitor: Build a new instance.
DefaultIterativeLinearSolverEvent - Class in org.apache.commons.math4.legacy.linear: A default concrete implementation of the abstract class IterativeLinearSolverEvent.
DefaultIterativeLinearSolverEvent(Object, int, RealVector, RealVector, double) - Constructor for class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Creates a new instance of this class.
DefaultIterativeLinearSolverEvent(Object, int, RealVector, RealVector, RealVector, double) - Constructor for class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Creates a new instance of this class.
DefaultMeasurementModel - Class in org.apache.commons.math4.legacy.filter: Default implementation of a MeasurementModel for the use with a KalmanFilter.
DefaultMeasurementModel(double[][], double[][]) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultMeasurementModel: Create a new MeasurementModel, taking double arrays as input parameters for the respective measurement matrix and noise.
DefaultMeasurementModel(RealMatrix, RealMatrix) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultMeasurementModel: Create a new MeasurementModel, taking RealMatrix objects as input parameters for the respective measurement matrix and noise.
DefaultProcessModel - Class in org.apache.commons.math4.legacy.filter: Default implementation of a ProcessModel for the use with a KalmanFilter.
DefaultProcessModel(double[][], double[][], double[][]) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Create a new ProcessModel, taking double arrays as input parameters.
DefaultProcessModel(double[][], double[][], double[][], double[], double[][]) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Create a new ProcessModel, taking double arrays as input parameters.
DefaultProcessModel(RealMatrix, RealMatrix, RealMatrix, RealVector, RealMatrix) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Create a new ProcessModel, taking double arrays as input parameters.
DefaultRealMatrixChangingVisitor - Class in org.apache.commons.math4.legacy.linear: Default implementation of the RealMatrixChangingVisitor interface.
DefaultRealMatrixChangingVisitor() - Constructor for class org.apache.commons.math4.legacy.linear.DefaultRealMatrixChangingVisitor
DefaultRealMatrixPreservingVisitor - Class in org.apache.commons.math4.legacy.linear: Default implementation of the RealMatrixPreservingVisitor interface.
DefaultRealMatrixPreservingVisitor() - Constructor for class org.apache.commons.math4.legacy.linear.DefaultRealMatrixPreservingVisitor
degree() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Returns the degree of the polynomial.
degree() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Returns the degree of the polynomial.
degree() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Returns the degree of the polynomial.
DEGREES_OF_FREEDOM - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
deleteLink(Neuron, Neuron) - Method in class org.apache.commons.math4.neuralnet.Network: Deletes the link between neurons a and b.
deleteNeuron(Neuron) - Method in class org.apache.commons.math4.neuralnet.Network: Deletes a neuron.
DENOMINATOR - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
DENOMINATOR_FORMAT - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
density(double) - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns the kernel density normalized so that its integral over each bin equals the bin mass.
density(double) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
density(double[]) - Method in class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution: Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
density(double[]) - Method in class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
density(double[]) - Method in interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution: Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
derivative(MultivariateDifferentiableFunction, int[]) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Convert an MultivariateDifferentiableFunction to an MultivariateFunction computing n^th order derivative.
derivative(UnivariateDifferentiableFunction, int) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Convert an UnivariateDifferentiableFunction to an UnivariateFunction computing n^th order derivative.
derivatives(T, int) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.FieldHermiteInterpolator: Interpolate value and first derivatives at a specified abscissa.
DerivativeStructure - Class in org.apache.commons.math4.legacy.analysis.differentiation: Class representing both the value and the differentials of a function.
DerivativeStructure(double, DerivativeStructure, double, DerivativeStructure) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Linear combination constructor.
DerivativeStructure(double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Linear combination constructor.
DerivativeStructure(double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Linear combination constructor.
DerivativeStructure(int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Build an instance with all values and derivatives set to 0.
DerivativeStructure(int, int, double) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Build an instance representing a constant value.
DerivativeStructure(int, int, double...) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Build an instance from all its derivatives.
DerivativeStructure(int, int, int, double) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Build an instance representing a variable.
DescriptiveStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data.
DescriptiveStatistics() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Construct a DescriptiveStatistics instance with an infinite window.
DescriptiveStatistics(double[]) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Construct a DescriptiveStatistics instance with an infinite window and the initial data values in initialDoubleArray.
DescriptiveStatistics(int) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Construct a DescriptiveStatistics instance with the specified window.
DescriptiveStatistics(Double[]) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Construct a DescriptiveStatistics instance with an infinite window and the initial data values in initialDoubleArray.
DescriptiveStatistics(DescriptiveStatistics) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Copy constructor.
deserializeRealMatrix(Object, String, ObjectInputStream) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Deserialize a RealMatrix field in a class.
deserializeRealVector(Object, String, ObjectInputStream) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Deserialize a RealVector field in a class.
df(double, double, double, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes approximate degrees of freedom for 2-sample t-test.
Dfp - Class in org.apache.commons.math4.legacy.core.dfp: Decimal floating point library for Java
Dfp(Dfp) - Constructor for class org.apache.commons.math4.legacy.core.dfp.Dfp: Copy constructor.
Dfp(DfpField) - Constructor for class org.apache.commons.math4.legacy.core.dfp.Dfp: Makes an instance with a value of zero.
Dfp(DfpField, byte) - Constructor for class org.apache.commons.math4.legacy.core.dfp.Dfp: Create an instance from a byte value.
Dfp(DfpField, byte, byte) - Constructor for class org.apache.commons.math4.legacy.core.dfp.Dfp: Creates an instance with a non-finite value.
Dfp(DfpField, double) - Constructor for class org.apache.commons.math4.legacy.core.dfp.Dfp: Create an instance from a double value.
Dfp(DfpField, int) - Constructor for class org.apache.commons.math4.legacy.core.dfp.Dfp: Create an instance from an int value.
Dfp(DfpField, long) - Constructor for class org.apache.commons.math4.legacy.core.dfp.Dfp: Create an instance from a long value.
Dfp(DfpField, String) - Constructor for class org.apache.commons.math4.legacy.core.dfp.Dfp: Create an instance from a String representation.
dfp2sci() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Convert an instance to a string using scientific notation.
dfp2string() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Convert an instance to a string using normal notation.
DfpDec - Class in org.apache.commons.math4.legacy.core.dfp: Subclass of Dfp which hides the radix-10000 artifacts of the superclass.
DfpDec(Dfp) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpDec: Copy constructor.
DfpDec(DfpField) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpDec: Makes an instance with a value of zero.
DfpDec(DfpField, byte) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpDec: Create an instance from a byte value.
DfpDec(DfpField, byte, byte) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpDec: Creates an instance with a non-finite value.
DfpDec(DfpField, double) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpDec: Create an instance from a double value.
DfpDec(DfpField, int) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpDec: Create an instance from an int value.
DfpDec(DfpField, long) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpDec: Create an instance from a long value.
DfpDec(DfpField, String) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpDec: Create an instance from a String representation.
DfpField - Class in org.apache.commons.math4.legacy.core.dfp: Field for Decimal floating point instances.
DfpField(int) - Constructor for class org.apache.commons.math4.legacy.core.dfp.DfpField: Create a factory for the specified number of radix digits.
DfpField.RoundingMode - Enum in org.apache.commons.math4.legacy.core.dfp: Enumerate for rounding modes.
DfpMath - Class in org.apache.commons.math4.legacy.core.dfp: Mathematical routines for use with Dfp.
DiagonalMatrix - Class in org.apache.commons.math4.legacy.linear: Implementation of a diagonal matrix.
DiagonalMatrix(double[]) - Constructor for class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Creates a matrix using the input array as the underlying data.
DiagonalMatrix(double[], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Creates a matrix using the input array as the underlying data.
DiagonalMatrix(int) - Constructor for class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Creates a matrix with the supplied dimension.
DIFFERENT_ORIG_AND_PERMUTED_DATA - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
DIFFERENT_ROWS_LENGTHS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
differentiate(double[]) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Returns the coefficients of the derivative of the polynomial with the given coefficients.
differentiate(UnivariateFunction) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Create an implementation of a differential from a regular function.
differentiate(UnivariateFunction) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateFunctionDifferentiator: Create an implementation of a differential from a regular function.
differentiate(UnivariateMatrixFunction) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Create an implementation of a differential from a regular matrix function.
differentiate(UnivariateMatrixFunction) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateMatrixFunctionDifferentiator: Create an implementation of a differential from a regular matrix function.
differentiate(UnivariateVectorFunction) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Create an implementation of a differential from a regular vector function.
differentiate(UnivariateVectorFunction) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateVectorFunctionDifferentiator: Create an implementation of a differential from a regular vector function.
DifferentiatorVectorMultivariateJacobianFunction - Class in org.apache.commons.math4.legacy.fitting.leastsquares: A MultivariateJacobianFunction (a thing that requires a derivative) combined with the thing that can find derivatives.
DifferentiatorVectorMultivariateJacobianFunction(MultivariateVectorFunction, UnivariateVectorFunctionDifferentiator) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.DifferentiatorVectorMultivariateJacobianFunction: Build the jacobian function using a differentiator.
DIGEST_NOT_INITIALIZED - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
DIMENSION - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
DimensionMismatchException - Exception in org.apache.commons.math4.legacy.exception: Exception to be thrown when two dimensions differ.
DimensionMismatchException(int, int) - Constructor for exception org.apache.commons.math4.legacy.exception.DimensionMismatchException: Construct an exception from the mismatched dimensions.
DimensionMismatchException(Localizable, int, int) - Constructor for exception org.apache.commons.math4.legacy.exception.DimensionMismatchException: Construct an exception from the mismatched dimensions.
DIMENSIONS_MISMATCH - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
DIMENSIONS_MISMATCH_2x2 - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
DIMENSIONS_MISMATCH_SIMPLE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
DISCRETE_CUMULATIVE_PROBABILITY_RETURNED_NAN - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
distance(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Calculates the L₂ (Euclidean) distance between two points.
distance(int[], int[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Calculates the L₂ (Euclidean) distance between two points.
distance(Clusterable, Clusterable) - Method in class org.apache.commons.math4.legacy.ml.clustering.Clusterer: Calculates the distance between two Clusterable instances with the configured DistanceMeasure.
distance1(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Calculates the L₁ (sum of abs) distance between two points.
distance1(int[], int[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Calculates the L₁ (sum of abs) distance between two points.
distanceInf(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Calculates the L_∞ (max of abs) distance between two points.
distanceInf(int[], int[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Calculates the L_∞ (max of abs) distance between two points.
DistanceMeasure - Interface in org.apache.commons.math4.legacy.ml.distance: Interface for distance measures of n-dimensional vectors.
DistanceMeasure - Interface in org.apache.commons.math4.neuralnet: Interface for distance measures between two n-dimensional vectors.
DISTRIBUTION_NOT_LOADED - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
divide(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: '÷' operator.
divide(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: '÷' operator.
divide(double) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: '÷' operator.
divide(double) - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: '÷' operator.
divide(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Perform division of two derivative structures.
divide(int) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Divide by a single digit less than radix.
divide(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Compute this ÷ a.
divide(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Compute this ÷ a.
divide(Dfp) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Divide this by divisor.
divide(BigReal) - Method in class org.apache.commons.math4.legacy.linear.BigReal: Compute this ÷ a.
divide(T) - Method in interface org.apache.commons.math4.legacy.core.FieldElement: Compute this ÷ a.
Divide - Class in org.apache.commons.math4.legacy.analysis.function: Divide the first operand by the second.
Divide() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Divide
DividedDifferenceInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Implements the Divided Difference Algorithm for interpolation of real univariate functions.
DividedDifferenceInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.DividedDifferenceInterpolator
doCopy() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Really copy the finalized instance.
doFinalize() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Really finalize the step.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.IterativeLegendreGaussIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.MidPointIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.RombergIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.SimpsonIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.TrapezoidIntegrator: Method for implementing actual integration algorithms in derived classes.
doIteration(SimplexTableau) - Method in class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Runs one iteration of the Simplex method on the given model.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.PowellOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.SimplexOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.univariate.BrentOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.univariate.MultiStartUnivariateOptimizer: Performs the bulk of the optimization algorithm.
DormandPrince54FieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 5(4) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince54FieldIntegrator(Field<T>, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Simple constructor.
DormandPrince54FieldIntegrator(Field<T>, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Simple constructor.
DormandPrince54Integrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 5(4) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince54Integrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54Integrator: Simple constructor.
DormandPrince54Integrator(double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54Integrator: Simple constructor.
DormandPrince853FieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 8(5,3) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince853FieldIntegrator(Field<T>, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Simple constructor.
DormandPrince853FieldIntegrator(Field<T>, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Simple constructor.
DormandPrince853Integrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 8(5,3) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince853Integrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853Integrator: Simple constructor.
DormandPrince853Integrator(double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853Integrator: Simple constructor.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BisectionSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.LaguerreSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver2: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.NewtonRaphsonSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.RiddersSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.SecantSolver: Method for implementing actual optimization algorithms in derived classes.
dotProduct(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the dot product.
dotProduct(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the dot product.
dotProduct(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Compute the dot product.
dotProduct(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Compute the dot product.
dotProduct(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Compute the dot product of this vector with v.
dotProduct(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Compute the dot product of this vector with v.
dotrap(int, String, Dfp, Dfp) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Raises a trap.
DoublePoint - Class in org.apache.commons.math4.legacy.ml.clustering: A simple implementation of Clusterable for points with double coordinates.
DoublePoint(double[]) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.DoublePoint: Build an instance wrapping an double array.
DoublePoint(int[]) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.DoublePoint: Build an instance wrapping an integer array.
doubleValue() - Method in class org.apache.commons.math4.legacy.linear.BigReal: Get the double value corresponding to the instance.
DOWN - org.apache.commons.math4.neuralnet.twod.NeuronSquareMesh2D.VerticalDirection: Row below the current row.
DOWNSIDE - org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance.Direction: The DOWNSIDE Direction is used to specify that the observations below.
DOWNSIDE_VARIANCE - Static variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: The DOWNSIDE Direction is used to specify that the observations below.
DSCompiler - Class in org.apache.commons.math4.legacy.analysis.differentiation: Class holding "compiled" computation rules for derivative structures.
DummyLocalizable - Class in org.apache.commons.math4.legacy.exception.util: Dummy implementation of the Localizable interface, without localization.
DummyLocalizable(String) - Constructor for class org.apache.commons.math4.legacy.exception.util.DummyLocalizable: Simple constructor.
DummyStepHandler - Class in org.apache.commons.math4.legacy.ode.sampling: This class is a step handler that does nothing.
DUPLICATED_ABSCISSA_DIVISION_BY_ZERO - org.apache.commons.math4.legacy.exception.util.LocalizedFormats

E

E - Static variable in class org.apache.commons.math4.core.jdkmath.AccurateMath: Napier's constant e, base of the natural logarithm.
E - Static variable in class org.apache.commons.math4.core.jdkmath.JdkMath: Constant.
EarthMoversDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the Earh Mover's distance (also known as Wasserstein metric) between two distributions.
EarthMoversDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.EarthMoversDistance
ebeAdd(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Creates an array whose contents will be the element-by-element addition of the arguments.
ebeDivide(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Creates an array whose contents will be the element-by-element division of the first argument by the second.
ebeDivide(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Element-by-element division.
ebeDivide(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Element-by-element division.
ebeDivide(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Element-by-element division.
ebeDivide(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Element-by-element division.
ebeDivide(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Element-by-element division.
ebeDivide(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Element-by-element division.
ebeDivide(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Element-by-element division.
ebeMultiply(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Creates an array whose contents will be the element-by-element multiplication of the arguments.
ebeMultiply(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Element-by-element multiplication.
ebeMultiply(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Element-by-element multiplication.
ebeMultiply(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Element-by-element multiplication.
ebeMultiply(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Element-by-element multiplication.
ebeSubtract(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Creates an array whose contents will be the element-by-element subtraction of the second argument from the first.
EDGE_CONNECTED_TO_ONE_FACET - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
EigenDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the eigen decomposition of a real matrix.
EigenDecomposition(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.linear.EigenDecomposition: Calculates the eigen decomposition of the symmetric tridiagonal matrix.
EigenDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.EigenDecomposition: Calculates the eigen decomposition of the given real matrix.
ELITISM_RATE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
ElitisticListPopulation - Class in org.apache.commons.math4.legacy.genetics: Population of chromosomes which uses elitism (certain percentage of the best chromosomes is directly copied to the next generation).
ElitisticListPopulation(int, double) - Constructor for class org.apache.commons.math4.legacy.genetics.ElitisticListPopulation: Creates a new ElitisticListPopulation instance and initializes its inner chromosome list.
ElitisticListPopulation(List<Chromosome>, int, double) - Constructor for class org.apache.commons.math4.legacy.genetics.ElitisticListPopulation: Creates a new ElitisticListPopulation instance.
ElkanKMeansPlusPlusClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Implementation of k-means++ algorithm.
ElkanKMeansPlusPlusClusterer(int) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.ElkanKMeansPlusPlusClusterer
ElkanKMeansPlusPlusClusterer(int, int, DistanceMeasure, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.ElkanKMeansPlusPlusClusterer
ElkanKMeansPlusPlusClusterer(int, int, DistanceMeasure, UniformRandomProvider, KMeansPlusPlusClusterer.EmptyClusterStrategy) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.ElkanKMeansPlusPlusClusterer
EmbeddedRungeKuttaFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the common part of all embedded Runge-Kutta integrators for Ordinary Differential Equations.
EmbeddedRungeKuttaFieldIntegrator(Field<T>, String, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Build a Runge-Kutta integrator with the given Butcher array.
EmbeddedRungeKuttaFieldIntegrator(Field<T>, String, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Build a Runge-Kutta integrator with the given Butcher array.
EmbeddedRungeKuttaIntegrator - Class in org.apache.commons.math4.legacy.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.math4.legacy.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.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Build a Runge-Kutta integrator with the given Butcher array.
EmpiricalDistribution - Class in org.apache.commons.math4.legacy.distribution: Represents an empirical probability distribution: Probability distribution derived from observed data without making any assumptions about the functional form of the population distribution that the data come from.
EMPTY_CLUSTER_IN_K_MEANS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
EMPTY_INTERPOLATION_SAMPLE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
EMPTY_POLYNOMIALS_COEFFICIENTS_ARRAY - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
EMPTY_SELECTED_COLUMN_INDEX_ARRAY - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
EMPTY_SELECTED_ROW_INDEX_ARRAY - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
EMPTY_STRING_FOR_IMAGINARY_CHARACTER - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
end() - Method in class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixChangingVisitor: End visiting a matrix.
end() - Method in class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixPreservingVisitor: End visiting a matrix.
end() - Method in class org.apache.commons.math4.legacy.linear.DefaultRealMatrixChangingVisitor: End visiting a matrix.
end() - Method in class org.apache.commons.math4.legacy.linear.DefaultRealMatrixPreservingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrixChangingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrixPreservingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.FieldVectorChangingVisitor: End visiting a vector.
end() - Method in interface org.apache.commons.math4.legacy.linear.FieldVectorPreservingVisitor: End visiting a vector.
end() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrixChangingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrixPreservingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.RealVectorChangingVisitor: End visiting a vector.
end() - Method in interface org.apache.commons.math4.legacy.linear.RealVectorPreservingVisitor: End visiting a vector.
ENDPOINTS_NOT_AN_INTERVAL - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
Entry() - Constructor for class org.apache.commons.math4.legacy.linear.RealVector.Entry: Simple constructor.
entrySetIterator() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Return an Iterator over the set of keys and values that have been added.
EnumeratedDistribution<T> - Class in org.apache.commons.math4.legacy.distribution: A generic implementation of a discrete probability distribution (Wikipedia) over a finite sample space, based on an enumerated list of <value, probability> pairs.
EnumeratedDistribution(List<Pair<T, Double>>) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedDistribution: Create an enumerated distribution using the given random number generator and probability mass function enumeration.
EnumeratedDistribution.Sampler - Class in org.apache.commons.math4.legacy.distribution: Sampler functionality.
EnumeratedIntegerDistribution - Class in org.apache.commons.math4.legacy.distribution: Implementation of an integer-valued EnumeratedDistribution.
EnumeratedIntegerDistribution(int[]) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: Create a discrete integer-valued distribution from the input data.
EnumeratedIntegerDistribution(int[], double[]) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: Create a discrete distribution.
EnumeratedRealDistribution - Class in org.apache.commons.math4.legacy.distribution: Implementation of a real-valued EnumeratedDistribution.
EnumeratedRealDistribution(double[]) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: Creates a discrete real-valued distribution from the input data.
EnumeratedRealDistribution(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: Create a discrete real-valued distribution using the given random number generator and probability mass function enumeration.
EQ - org.apache.commons.math4.legacy.optim.linear.Relationship: Equality relationship.
EQUAL_VERTICES_IN_SIMPLEX - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
equals(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Returns true iff both arguments are null or have same dimensions and all their elements are equal as defined by Precision.equals(double,double).
equals(float[], float[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Returns true iff both arguments are null or have same dimensions and all their elements are equal as defined by Precision.equals(float,float).
equals(Object) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Test for the equality of two derivative structures.
equals(Object) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Test for the equality of two sparse gradients.
equals(Object) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction
equals(Object) - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Check if instance is equal to x.
equals(Object) - Method in class org.apache.commons.math4.legacy.core.Pair: Compare the specified object with this entry for equality.
equals(Object) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix
equals(Object) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.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.math4.legacy.linear.ArrayFieldVector: Test for the equality of two vectors.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Test for the equality of two real vectors.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.BigReal
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Test for the equality of two real vectors.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Test for the equality of two real vectors.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector
equals(Object) - Method in class org.apache.commons.math4.legacy.ml.clustering.DoublePoint
equals(Object) - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraint
equals(Object) - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction
equals(Object) - Method in class org.apache.commons.math4.legacy.optim.PointValuePair
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Returns true iff object is the same type of StorelessUnivariateStatistic (the object's class equals this instance) returning the same values as this for getResult() and getN().
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialMean
equals(Object) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns true iff o is a PSquarePercentile returning the.
equals(Object) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.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.math4.legacy.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.math4.legacy.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.math4.legacy.stat.Frequency
equalSidesAlongAxes(int, double) - Static method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Builds simplex with the given side length.
equalsIncludingNaN(double[], double[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Returns true iff both arguments are null or have same dimensions and all their elements are equal as defined by this method.
equalsIncludingNaN(float[], float[]) - Static method in class org.apache.commons.math4.legacy.core.MathArrays: Returns true iff both arguments are null or have same dimensions and all their elements are equal as defined by this method.
EquationsMapper - Class in org.apache.commons.math4.legacy.ode: Class mapping the part of a complete state or derivative that pertains to a specific differential equation.
EquationsMapper(int, int) - Constructor for class org.apache.commons.math4.legacy.ode.EquationsMapper: simple constructor.
ERR_SCALE - Static variable in class org.apache.commons.math4.legacy.core.dfp.Dfp: The amount under/overflows are scaled by before going to trap handler.
ERROR - org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer.EmptyClusterStrategy: Generate an error.
estimate(double[][], int) - Static method in class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Helper method to create a multivariate normal mixture model which can be used to initialize MultivariateNormalMixtureExpectationMaximization.fit(MixtureMultivariateNormalDistribution).
estimate(double[], int[], double, int, KthSelector) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Estimation based on K^th selection.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54Integrator: Compute the error ratio.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853Integrator: Compute the error ratio.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Compute the error ratio.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54Integrator: Compute the error ratio.
estimateError(T[][], T[], T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Compute the error ratio.
estimateError(T[][], T[], T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Compute the error ratio.
estimateError(T[][], T[], T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Compute the error ratio.
estimateError(T[][], T[], T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Compute the error ratio.
estimateErrorVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the variance of the error.
estimateRegressandVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Returns the variance of the regressand, ie Var(y).
estimateRegressandVariance() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Returns the variance of the regressand, ie Var(y).
estimateRegressionParameters() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the regression parameters b.
estimateRegressionParameters() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Estimates the regression parameters b.
estimateRegressionParametersStandardErrors() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Returns the standard errors of the regression parameters.
estimateRegressionParametersStandardErrors() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Returns the standard errors of the regression parameters.
estimateRegressionParametersVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the variance of the regression parameters, ie Var(b).
estimateRegressionParametersVariance() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Estimates the variance of the regression parameters, ie Var(b).
estimateRegressionStandardError() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the standard error of the regression.
estimateResiduals() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the residuals, ie u = y - X*b.
estimateResiduals() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Estimates the residuals, ie u = y - X*b.
EuclideanDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the L₂ (Euclidean) distance between two points.
EuclideanDistance - Class in org.apache.commons.math4.neuralnet: Euclidean distance measures of n-dimensional vectors.
EuclideanDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.EuclideanDistance
EuclideanDistance() - Constructor for class org.apache.commons.math4.neuralnet.EuclideanDistance
EULER_ANGLES_SINGULARITY - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
EulerFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements a simple Euler integrator for Ordinary Differential Equations.
EulerFieldIntegrator(Field<T>, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Simple constructor.
EulerIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements a simple Euler integrator for Ordinary Differential Equations.
EulerIntegrator(double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EulerIntegrator: Simple constructor.
evaluate() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Returns the result of evaluating the statistic over the stored data.
evaluate(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns the result of evaluating the statistic over the stored data.
evaluate(double[]) - Method in interface org.apache.commons.math4.legacy.core.MathArrays.Function: Operates on an entire array.
evaluate(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: This default implementation creates a copy of this StorelessUnivariateStatistic instance, calls AbstractStorelessUnivariateStatistic.clear() on it, then calls AbstractStorelessUnivariateStatistic.incrementAll(double[]) with the specified portion of the input array, and then uses AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
evaluate(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Returns the result of evaluating the statistic over the input array.
evaluate(double[]) - Method in class org.apache.commons.math4.legacy.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[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the variance of the entries in the input array, or Double.NaN if the array is empty.
evaluate(double[]) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.UnivariateStatistic: Returns the result of evaluating the statistic over the input array.
evaluate(double[], double) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument.
evaluate(double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns the SemiVariance of the designated values against the cutoff, using instance properties variancDirection and biasCorrection.
evaluate(double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns the Standard Deviation of the entries in the input array, using the precomputed mean value.
evaluate(double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the variance of the entries in the input array, using the precomputed mean value.
evaluate(double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the pth percentile of the values in the values array.
evaluate(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Returns the weighted arithmetic mean of the entries in the input array.
evaluate(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the weighted variance of the entries in the input array.
evaluate(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Returns the weighted product of the entries in the input array.
evaluate(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: The weighted sum of the entries in the input array.
evaluate(double[], double[]) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.WeightedEvaluation: Returns the result of evaluating the statistic over the input array, using the supplied weights.
evaluate(double[], double[], double) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Evaluate the Lagrange polynomial using Neville's Algorithm.
evaluate(double[], double[], double) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Evaluate the Newton polynomial using nested multiplication.
evaluate(double[], double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the weighted variance of the values in the input array, using the precomputed weighted mean value.
evaluate(double[], double[], double) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Evaluate weighted percentile by estimation rule specified in Percentile.EstimationType.
evaluate(double[], double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the pth percentile of the values in the values array with their weights.
evaluate(double[], double[], double, int, int) - Method in class org.apache.commons.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the weighted quantileth percentile of the designated values in the values array.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: The weighted sum of the entries in the specified portion of the input array, or 0 if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in interface org.apache.commons.math4.legacy.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[], double[], int, int, double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the pth percentile of the values in the values array with sampleWeights, starting with the element in (0-based) position begin in the array and including length values.
evaluate(double[], double, int, int) - Method in class org.apache.commons.math4.legacy.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, int, int) - Method in class org.apache.commons.math4.legacy.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, SemiVariance.Direction) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.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[], double, KthSelector) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Evaluate method to compute the percentile for a given bounded array.
evaluate(double[], int[], double, KthSelector) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Evaluate method to compute the percentile for a given bounded array using earlier computed pivots heap.
This basically calls the index and then estimate functions to return the estimated percentile value.
evaluate(double[], int, int) - Method in interface org.apache.commons.math4.legacy.core.MathArrays.Function
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: This default implementation creates a copy of this StorelessUnivariateStatistic instance, calls AbstractStorelessUnivariateStatistic.clear() on it, then calls AbstractStorelessUnivariateStatistic.incrementAll(double[]) with the specified portion of the input array, and then uses AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.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.math4.legacy.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.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns the SemiVariance of the designated values against the mean, using instance properties varianceDirection and biasCorrection.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Returns the Skewness of the entries in the specified portion of the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the quantileth percentile of the designated values in the values array.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.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[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: The sum of the entries in the specified portion of the input array, or 0 if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.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.math4.legacy.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[], int, int) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.UnivariateStatistic: Returns the result of evaluating the statistic over the specified entries in the input array.
evaluate(double[], int, int, double) - Method in class org.apache.commons.math4.legacy.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[], SemiVariance.Direction) - Method in class org.apache.commons.math4.legacy.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(MultivariateFunction, Comparator<PointValuePair>) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Evaluates the (non-evaluated) simplex points and returns a new instance with vertices sorted from best to worst.
evaluate(RealVector) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Evaluate the model at the specified point.
evaluate(RealVector) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem: Evaluate the model at the specified point.
evaluateStep(FieldStepInterpolator<T>) - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Evaluate the impact of the proposed step on the event handler.
evaluateStep(StepInterpolator) - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Evaluate the impact of the proposed step on the event handler.
EVALUATION - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
evaluationChecker(ConvergenceChecker<PointVectorValuePair>) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: View a convergence checker specified for a PointVectorValuePair as one specified for an LeastSquaresProblem.Evaluation.
EvaluationRmsChecker - Class in org.apache.commons.math4.legacy.fitting.leastsquares: Check if an optimization has converged based on the change in computed RMS.
EvaluationRmsChecker(double) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.EvaluationRmsChecker: Create a convergence checker for the RMS with the same relative and absolute tolerance.
EvaluationRmsChecker(double, double) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.EvaluationRmsChecker: Create a convergence checker for the RMS with a relative and absolute tolerance.
EVALUATIONS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
EventFilter - Class in org.apache.commons.math4.legacy.ode.events: Wrapper used to detect only increasing or decreasing events.
EventFilter(EventHandler, FilterType) - Constructor for class org.apache.commons.math4.legacy.ode.events.EventFilter: Wrap an event handler.
EventHandler - Interface in org.apache.commons.math4.legacy.ode.events: This interface represents a handler for discrete events triggered during ODE integration.
EventHandler.Action - Enum in org.apache.commons.math4.legacy.ode.events: Enumerate for actions to be performed when an event occurs.
eventOccurred(double, double[], boolean) - Method in class org.apache.commons.math4.legacy.ode.events.EventFilter: Handle an event and choose what to do next.
eventOccurred(double, double[], boolean) - Method in interface org.apache.commons.math4.legacy.ode.events.EventHandler: Handle an event and choose what to do next.
eventOccurred(FieldODEStateAndDerivative<T>, boolean) - Method in interface org.apache.commons.math4.legacy.ode.events.FieldEventHandler: Handle an event and choose what to do next.
EventState - Class in org.apache.commons.math4.legacy.ode.events: This class handles the state for one event handler during integration steps.
EventState(EventHandler, double, double, int, UnivariateSolver) - Constructor for class org.apache.commons.math4.legacy.ode.events.EventState: Simple constructor.
evolve(Population, StoppingCondition) - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Evolve the given population.
exactP(double, int, int, boolean) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
exactP(double, int, int, boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes \(P(D_{n,m} > d)\) if strict is true; otherwise \(P(D_{n,m} \ge d)\), where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic.
ExceptionContext - Class in org.apache.commons.math4.legacy.exception.util: Class that contains the actual implementation of the functionality mandated by the ExceptionContext interface.
ExceptionContext(Throwable) - Constructor for class org.apache.commons.math4.legacy.exception.util.ExceptionContext: Simple constructor.
ExceptionContextProvider - Interface in org.apache.commons.math4.legacy.exception.util: Interface for accessing the context data structure stored in Commons Math exceptions.
exp - Variable in class org.apache.commons.math4.legacy.core.dfp.Dfp: Exponent.
exp() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Exponential.
exp() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Exponential.
exp() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Exponential.
exp() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Exponential.
exp(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Exponential function.
exp(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
exp(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute exponential of a derivative structure.
exp(Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpMath: Computes e to the given power.
Exp - Class in org.apache.commons.math4.legacy.analysis.function: Exponential function.
Exp() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Exp
ExpandableStatefulODE - Class in org.apache.commons.math4.legacy.ode: This class represents a combined set of first order differential equations, with at least a primary set of equations expandable by some sets of secondary equations.
ExpandableStatefulODE(FirstOrderDifferentialEquations) - Constructor for class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Build an expandable set from its primary ODE set.
EXPANSION_FACTOR_SMALLER_THAN_ONE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
expInternal(Dfp) - Static method in class org.apache.commons.math4.legacy.core.dfp.DfpMath: Computes e to the given power.
expm1() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Exponential minus 1.
expm1() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Exponential minus 1.
expm1() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Exponential minus 1.
expm1() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Exponential minus 1.
expm1(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Compute exp(x) - 1.
expm1(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
expm1(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute exp(x) - 1 of a derivative structure.
Expm1 - Class in org.apache.commons.math4.legacy.analysis.function: e^x-1 function.
Expm1() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Expm1
EXPONENT - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
exponentialDecay(double, double, long) - Static method in class org.apache.commons.math4.neuralnet.sofm.LearningFactorFunctionFactory: Creates an exponential decay function.
exponentialDecay(double, double, long) - Static method in class org.apache.commons.math4.neuralnet.sofm.NeighbourhoodSizeFunctionFactory: Creates an exponential decay function.
ExponentialDecayFunction - Class in org.apache.commons.math4.neuralnet.sofm.util: Exponential decay function: a e^{-x / b}, where x is the (integer) independent variable.
ExponentialDecayFunction(double, double, long) - Constructor for class org.apache.commons.math4.neuralnet.sofm.util.ExponentialDecayFunction: Creates an instance.
extractEquationData(double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.EquationsMapper: Extract equation data from a complete state or derivative array.
extractEquationData(int, T[]) - Method in class org.apache.commons.math4.legacy.ode.FieldEquationsMapper: Extract equation data from a complete state or derivative array.
extractField(T[]) - Static method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the elements type from an array.
extractField(T[][]) - Static method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the elements type from an array.

F

FACET_ORIENTATION_MISMATCH - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FACTORIAL_NEGATIVE_PARAMETER - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FAILED - org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: NaNs result in an exception.
FAILED_BRACKETING - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FAILED_FRACTION_CONVERSION - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FARTHEST_POINT - org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer.EmptyClusterStrategy: Create a cluster around the point farthest from its centroid.
FastCosineTransform - Class in org.apache.commons.math4.transform: Implements the Fast Cosine Transform for transformation of one-dimensional real data sets.
FastCosineTransform(FastCosineTransform.Norm) - Constructor for class org.apache.commons.math4.transform.FastCosineTransform
FastCosineTransform(FastCosineTransform.Norm, boolean) - Constructor for class org.apache.commons.math4.transform.FastCosineTransform
FastCosineTransform.Norm - Enum in org.apache.commons.math4.transform: Normalization types.
FastFourierTransform - Class in org.apache.commons.math4.transform: Implements the Fast Fourier Transform for transformation of one-dimensional real or complex data sets.
FastFourierTransform(FastFourierTransform.Norm) - Constructor for class org.apache.commons.math4.transform.FastFourierTransform
FastFourierTransform(FastFourierTransform.Norm, boolean) - Constructor for class org.apache.commons.math4.transform.FastFourierTransform
FastFourierTransform.Norm - Enum in org.apache.commons.math4.transform: Normalization types.
FastHadamardTransform - Class in org.apache.commons.math4.transform: Fast Hadamard Transform (FHT).
FastHadamardTransform() - Constructor for class org.apache.commons.math4.transform.FastHadamardTransform: Default constructor.
FastHadamardTransform(boolean) - Constructor for class org.apache.commons.math4.transform.FastHadamardTransform
FastSineTransform - Class in org.apache.commons.math4.transform: Implements the Fast Sine Transform for transformation of one-dimensional real data sets.
FastSineTransform(FastSineTransform.Norm) - Constructor for class org.apache.commons.math4.transform.FastSineTransform
FastSineTransform(FastSineTransform.Norm, boolean) - Constructor for class org.apache.commons.math4.transform.FastSineTransform
FastSineTransform.Norm - Enum in org.apache.commons.math4.transform: Normalization types.
FeatureInitializer - Interface in org.apache.commons.math4.neuralnet: Defines how to assign the first value of a neuron's feature.
FeatureInitializerFactory - Class in org.apache.commons.math4.neuralnet: Creates functions that will select the initial values of a neuron's features.
Field<T> - Interface in org.apache.commons.math4.legacy.core: Interface representing a field.
FieldBracketingNthOrderBrentSolver<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.analysis.solvers: This class implements a modification of the Brent algorithm.
FieldBracketingNthOrderBrentSolver(T, T, T, int) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Construct a solver.
FieldButcherArrayProvider<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.nonstiff: This interface represents an integrator based on Butcher arrays.
FieldDecompositionSolver<T> - Interface in org.apache.commons.math4.legacy.field.linalg: Interface handling decomposition algorithms that can solve A X = B.
FieldDecompositionSolver<T extends FieldElement<T>> - Interface in org.apache.commons.math4.legacy.linear: Interface handling decomposition algorithms that can solve A × X = B.
FieldDenseMatrix<T> - Class in org.apache.commons.math4.legacy.field.linalg: Square matrix whose elements define a Field.
FieldElement<T> - Interface in org.apache.commons.math4.legacy.core: Interface representing field elements.
FieldEquationsMapper<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: Class mapping the part of a complete state or derivative that pertains to a set of differential equations.
FieldEventHandler<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.events: This interface represents a handler for discrete events triggered during ODE integration.
FieldEventState<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.events: This class handles the state for one event handler during integration steps.
FieldEventState(FieldEventHandler<T>, double, T, int, BracketedRealFieldUnivariateSolver<T>) - Constructor for class org.apache.commons.math4.legacy.ode.events.FieldEventState: Simple constructor.
FieldExpandableODE<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: This class represents a combined set of first order differential equations, with at least a primary set of equations expandable by some sets of secondary equations.
FieldExpandableODE(FirstOrderFieldDifferentialEquations<T>) - Constructor for class org.apache.commons.math4.legacy.ode.FieldExpandableODE: Build an expandable set from its primary ODE set.
FieldFixedStepHandler<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents a handler that should be called after each successful fixed step.
FieldHermiteInterpolator<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.analysis.interpolation: Polynomial interpolator using both sample values and sample derivatives.
FieldHermiteInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.FieldHermiteInterpolator: Create an empty interpolator.
FieldLUDecomposition<T> - Class in org.apache.commons.math4.legacy.field.linalg: Calculates the LUP-decomposition of a square matrix.
FieldLUDecomposition<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Calculates the LUP-decomposition of a square matrix.
FieldLUDecomposition(FieldMatrix<T>) - Constructor for class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Calculates the LU-decomposition of the given matrix.
FieldMatrix<T extends FieldElement<T>> - Interface in org.apache.commons.math4.legacy.linear: Interface defining field-valued matrix with basic algebraic operations.
FieldMatrixChangingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math4.legacy.linear: Interface defining a visitor for matrix entries.
FieldMatrixPreservingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math4.legacy.linear: Interface defining a visitor for matrix entries.
FieldODEState<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: Container for time, main and secondary state vectors.
FieldODEState(T, T[]) - Constructor for class org.apache.commons.math4.legacy.ode.FieldODEState: Simple constructor.
FieldODEState(T, T[], T[][]) - Constructor for class org.apache.commons.math4.legacy.ode.FieldODEState: Simple constructor.
FieldODEStateAndDerivative<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: Container for time, main and secondary state vectors as well as their derivatives.
FieldODEStateAndDerivative(T, T[], T[]) - Constructor for class org.apache.commons.math4.legacy.ode.FieldODEStateAndDerivative: Simple constructor.
FieldODEStateAndDerivative(T, T[], T[], T[][], T[][]) - Constructor for class org.apache.commons.math4.legacy.ode.FieldODEStateAndDerivative: Simple constructor.
FieldSecondaryEquations<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode: This interface allows users to add secondary differential equations to a primary set of differential equations.
FieldStepHandler<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents a handler that should be called after each successful step.
FieldStepInterpolator<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents an interpolator over the last step during an ODE integration.
FieldStepNormalizer<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.sampling: This class wraps an object implementing FieldFixedStepHandler into a FieldStepHandler.
FieldStepNormalizer(double, FieldFixedStepHandler<T>) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Simple constructor.
FieldStepNormalizer(double, FieldFixedStepHandler<T>, StepNormalizerBounds) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Simple constructor.
FieldStepNormalizer(double, FieldFixedStepHandler<T>, StepNormalizerMode) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Simple constructor.
FieldStepNormalizer(double, FieldFixedStepHandler<T>, StepNormalizerMode, StepNormalizerBounds) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Simple constructor.
FieldVector<T extends FieldElement<T>> - Interface in org.apache.commons.math4.legacy.linear: Interface defining a field-valued vector with basic algebraic operations.
FieldVectorChangingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math4.legacy.linear: This interface defines a visitor for the entries of a vector.
FieldVectorPreservingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math4.legacy.linear: This interface defines a visitor for the entries of a vector.
fill(T) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Sets all elements to the given value.
filterStep(double, boolean, boolean) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Filter the integration step.
filterStep(T, boolean, boolean) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Filter the integration step.
FilterType - Enum in org.apache.commons.math4.legacy.ode.events: Enumerate for filtering events.
finalizeStep() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Finalize the step.
findMaxY(WeightedObservedPoint[]) - Method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter.ParameterGuesser: Finds index of point in specified points with the largest Y.
findSameChromosome(Population) - Method in class org.apache.commons.math4.legacy.genetics.Chromosome: Searches the population for another chromosome with the same representation.
FINITE - Static variable in class org.apache.commons.math4.legacy.core.dfp.Dfp: Indicator value for normal finite numbers.
FiniteDifferencesDifferentiator - Class in org.apache.commons.math4.legacy.analysis.differentiation: Univariate functions differentiator using finite differences.
FiniteDifferencesDifferentiator(int, double) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Build a differentiator with number of points and step size when independent variable is unbounded.
FiniteDifferencesDifferentiator(int, double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Build a differentiator with number of points and step size when independent variable is bounded.
fireInitializationEvent(IterationEvent) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Informs all registered listeners that the initial phase (prior to the main iteration loop) has been completed.
fireIterationPerformedEvent(IterationEvent) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Informs all registered listeners that a new iteration (in the main iteration loop) has been performed.
fireIterationStartedEvent(IterationEvent) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Informs all registered listeners that a new iteration (in the main iteration loop) has been started.
fireTerminationEvent(IterationEvent) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Informs all registered listeners that the final phase (post-iterations) has been completed.
FIRST - org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Include the first point, but not the last point.
FIRST_COLUMNS_NOT_INITIALIZED_YET - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FIRST_ELEMENT_NOT_ZERO - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FIRST_ROWS_NOT_INITIALIZED_YET - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
firstIncluded() - Method in enum org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Returns a value indicating whether the first point should be passed to the underlying fixed step size step handler.
FirstOrderConverter - Class in org.apache.commons.math4.legacy.ode: This class converts second order differential equations to first order ones.
FirstOrderConverter(SecondOrderDifferentialEquations) - Constructor for class org.apache.commons.math4.legacy.ode.FirstOrderConverter: Simple constructor.
FirstOrderDifferentialEquations - Interface in org.apache.commons.math4.legacy.ode: This interface represents a first order differential equations set.
FirstOrderFieldDifferentialEquations<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode: This interface represents a first order differential equations set.
FirstOrderFieldIntegrator<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode: This interface represents a first order integrator for differential equations.
FirstOrderIntegrator - Interface in org.apache.commons.math4.legacy.ode: This interface represents a first order integrator for differential equations.
fit(Collection<WeightedObservedPoint>) - Method in class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter: Fits a curve.
fit(MixtureMultivariateNormalDistribution) - Method in class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Fit a mixture model to the data supplied to the constructor.
fit(MixtureMultivariateNormalDistribution, int, double) - Method in class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Fit a mixture model to the data supplied to the constructor.
fitness() - Method in interface org.apache.commons.math4.legacy.genetics.Fitness: Compute the fitness.
Fitness - Interface in org.apache.commons.math4.legacy.genetics: Fitness of a chromosome.
fix1stArgument(BivariateFunction, double) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Creates a unary function by fixing the first argument of a binary function.
fix2ndArgument(BivariateFunction, double) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Creates a unary function by fixing the second argument of a binary function.
FIXED - org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: NaNs are left in place.
FixedElapsedTime - Class in org.apache.commons.math4.legacy.genetics: Stops after a fixed amount of time has elapsed.
FixedElapsedTime(long) - Constructor for class org.apache.commons.math4.legacy.genetics.FixedElapsedTime: Create a new FixedElapsedTime instance.
FixedElapsedTime(long, TimeUnit) - Constructor for class org.apache.commons.math4.legacy.genetics.FixedElapsedTime: Create a new FixedElapsedTime instance.
FixedGenerationCount - Class in org.apache.commons.math4.legacy.genetics: Stops after a fixed number of generations.
FixedGenerationCount(int) - Constructor for class org.apache.commons.math4.legacy.genetics.FixedGenerationCount: Create a new FixedGenerationCount instance.
FixedStepHandler - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents a handler that should be called after each successful fixed step.
FLAG_DIV_ZERO - Static variable in class org.apache.commons.math4.legacy.core.dfp.DfpField: IEEE 854-1987 flag for division by zero.
FLAG_INEXACT - Static variable in class org.apache.commons.math4.legacy.core.dfp.DfpField: IEEE 854-1987 flag for inexact result.
FLAG_INVALID - Static variable in class org.apache.commons.math4.legacy.core.dfp.DfpField: IEEE 854-1987 flag for invalid operation.
FLAG_OVERFLOW - Static variable in class org.apache.commons.math4.legacy.core.dfp.DfpField: IEEE 854-1987 flag for overflow.
FLAG_UNDERFLOW - Static variable in class org.apache.commons.math4.legacy.core.dfp.DfpField: IEEE 854-1987 flag for underflow.
flatten(Object[]) - Static method in class org.apache.commons.math4.legacy.exception.util.ArgUtils: Transform a multidimensional array into a one-dimensional list.
FLETCHER_REEVES - org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.Formula: Fletcher-Reeves formula.
floor() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get the largest whole number smaller than instance.
floor() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Get the largest whole number smaller than instance.
floor() - Method in class org.apache.commons.math4.legacy.core.dfp.Dfp: Round to an integer using the round floor mode.
floor() - Method in interface org.apache.commons.math4.legacy.core.RealFieldElement: Get the largest whole number smaller than instance.
floor(double) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Get the largest whole number smaller than x.
floor(double) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
Floor - Class in org.apache.commons.math4.legacy.analysis.function: floor function.
Floor() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Floor
floorDiv(int, int) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Finds q such that a = q b + r with 0 <= r < b if b > 0 and b < r <= 0 if b < 0.
floorDiv(int, int) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
floorDiv(long, long) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Finds q such that a = q b + r with 0 <= r < b if b > 0 and b < r <= 0 if b < 0.
floorDiv(long, long) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
floorMod(int, int) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Finds r such that a = q b + r with 0 <= r < b if b > 0 and b < r <= 0 if b < 0.
floorMod(int, int) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
floorMod(long, long) - Static method in class org.apache.commons.math4.core.jdkmath.AccurateMath: Finds r such that a = q b + r with 0 <= r < b if b > 0 and b < r <= 0 if b < 0.
floorMod(long, long) - Static method in class org.apache.commons.math4.core.jdkmath.JdkMath
forceSide(int, UnivariateFunction, BracketedUnivariateSolver<UnivariateFunction>, double, double, double, AllowedSolution) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Force a root found by a non-bracketing solver to lie on a specified side, as if the solver were a bracketing one.
format(Double) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: This method calls ComplexFormat.format(Object,StringBuffer,FieldPosition).
format(Object, StringBuffer, FieldPosition) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Formats a object to produce a string.
format(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: This method calls RealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition).
format(RealMatrix, StringBuffer, FieldPosition) - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Formats a RealMatrix object to produce a string.
format(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: This method calls RealVectorFormat.format(RealVector,StringBuffer,FieldPosition).
format(RealVector, StringBuffer, FieldPosition) - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Formats a RealVector object to produce a string.
format(Complex) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: This method calls ComplexFormat.format(Object,StringBuffer,FieldPosition).
format(Complex, StringBuffer, FieldPosition) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Formats a Complex object to produce a string.
formatDouble(double, NumberFormat, StringBuffer, FieldPosition) - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Formats a double value to produce a string.
fraction(double, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Create a fraction.
fraction(int, int) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Create a fraction.
fraction(int, int) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaFieldIntegrator: Create a fraction.
FRACTION - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FRACTION_CONVERSION_OVERFLOW - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
Frequency<T extends Comparable<T>> - Class in org.apache.commons.math4.legacy.stat: Maintains a frequency distribution.
Frequency() - Constructor for class org.apache.commons.math4.legacy.stat.Frequency: Default constructor.
Frequency(Comparator<T>) - Constructor for class org.apache.commons.math4.legacy.stat.Frequency: Constructor allowing values Comparator to be specified.
from(int, double[]) - Static method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Factory that creates a new instance from the specified data.
from(int, double[], Function<SummaryStatistics, ContinuousDistribution>) - Static method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Factory that creates a new instance from the specified data.
from(int, long[], double[][], long[][]) - Static method in class org.apache.commons.math4.neuralnet.Network: Builds a network from a list of neurons and their neighbours.
function(DoubleUnaryOperator, double, double) - Static method in class org.apache.commons.math4.neuralnet.FeatureInitializerFactory: Creates an initializer from a univariate function f(x).
FUNCTION - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FUNCTION_NOT_DIFFERENTIABLE - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FUNCTION_NOT_POLYNOMIAL - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
FunctionUtils - Class in org.apache.commons.math4.legacy.analysis: Utilities for manipulating function objects.
FuzzyKMeansClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Fuzzy K-Means clustering algorithm.
FuzzyKMeansClusterer(int, double) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Creates a new instance of a FuzzyKMeansClusterer.
FuzzyKMeansClusterer(int, double, int, DistanceMeasure) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Creates a new instance of a FuzzyKMeansClusterer.
FuzzyKMeansClusterer(int, double, int, DistanceMeasure, double, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Creates a new instance of a FuzzyKMeansClusterer.

G

g(double[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Computes the G statistic for Goodness of Fit comparing observed and expected frequency counts.
g(double[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
g(double, double[]) - Method in class org.apache.commons.math4.legacy.ode.events.EventFilter: Compute the value of the switching function.
g(double, double[]) - Method in interface org.apache.commons.math4.legacy.ode.events.EventHandler: Compute the value of the switching function.
g(FieldODEStateAndDerivative<T>) - Method in interface org.apache.commons.math4.legacy.ode.events.FieldEventHandler: Compute the value of the switching function.
gaussian(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.random.CorrelatedVectorFactory
Gaussian - Class in org.apache.commons.math4.legacy.analysis.function: Gaussian function.
Gaussian() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Gaussian: Normalized gaussian with zero mean and unit standard deviation.
Gaussian(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Gaussian: Normalized gaussian with given mean and standard deviation.
Gaussian(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Gaussian: Gaussian with given normalization factor, mean and standard deviation.
Gaussian.Parametric - Class in org.apache.commons.math4.legacy.analysis.function: Parametric function where the input array contains the parameters of the Gaussian.
GaussianCurveFitter - Class in org.apache.commons.math4.legacy.fitting: Fits points to a Gaussian function.
GaussianCurveFitter.ParameterGuesser - Class in org.apache.commons.math4.legacy.fitting: Guesses the parameters norm, mean, and sigma of a Gaussian.Parametric based on the specified observed points.
GaussIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Class that implements the Gaussian rule for integrating a weighted function.
GaussIntegrator(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegrator: Creates an integrator from the given points and weights.
GaussIntegrator(Pair<double[], double[]>) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegrator: Creates an integrator from the given pair of points (first element of the pair) and weights (second element of the pair.
GaussIntegratorFactory - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Class that provides different ways to compute the nodes and weights to be used by the Gaussian integration rule.
GaussIntegratorFactory() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegratorFactory
GaussNewtonOptimizer - Class in org.apache.commons.math4.legacy.fitting.leastsquares: Gauss-Newton least-squares solver.
GaussNewtonOptimizer() - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer: Creates a Gauss Newton optimizer.
GaussNewtonOptimizer(GaussNewtonOptimizer.Decomposition) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer: Create a Gauss Newton optimizer that uses the given decomposition algorithm to solve the normal equations.
GaussNewtonOptimizer.Decomposition - Enum in org.apache.commons.math4.legacy.fitting.leastsquares: The decomposition algorithm to use to solve the normal equations.
GCD_OVERFLOW_32_BITS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
GCD_OVERFLOW_64_BITS - org.apache.commons.math4.legacy.exception.util.LocalizedFormats
gDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts in observed1 and observed2.
gDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
GeneticAlgorithm - Class in org.apache.commons.math4.legacy.genetics: Implementation of a genetic algorithm.
GeneticAlgorithm(CrossoverPolicy, double, MutationPolicy, double, SelectionPolicy) - Constructor for class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Create a new genetic algorithm.
geometricMean(double[]) - Static method in class org.apache.commons.math4.legacy.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.math4.legacy.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.
GeometricMean - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Returns the geometric mean of the available values.
GeometricMean() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Create a GeometricMean instance.
GeometricMean(GeometricMean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Copy constructor, creates a new GeometricMean identical to the original.
GeometricMean(SumOfLogs) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Create a GeometricMean instance using the given SumOfLogs instance.
GEQ - org.apache.commons.math4.legacy.optim.linear.Relationship: Greater than or equal relationship.
get() - Method in class org.apache.commons.math4.legacy.random.HaltonSequenceGenerator
get() - Method in class org.apache.commons.math4.legacy.random.SobolSequenceGenerator
get(int) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Retrieves a copy of the simplex point stored at index.
get(int, int) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Gets an element.
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in interface org.apache.commons.math4.legacy.ode.nonstiff.FieldButcherArrayProvider: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getAbsoluteAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Get the absolute accuracy.
getAbsoluteAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator: Get the absolute accuracy.
getAbsoluteAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Get the absolute accuracy of the solver.
getAbsoluteAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Get the absolute accuracy of the solver.
getAbsoluteAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedRealFieldUnivariateSolver: Get the absolute accuracy of the solver.
getAbsoluteAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Get the absolute accuracy.
getAbsoluteThreshold() - Method in class org.apache.commons.math4.legacy.optim.AbstractConvergenceChecker
getAdjustedRSquared() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the adjusted R-squared statistic, defined by the formula R²_adj = 1 - [SSR (n - 1)] / [SSTO (n - p)] where SSR is the sum of squared residuals}, SSTO is the total sum of squares}, n is the number of observations and p is the number of parameters estimated (including the intercept).
getAgrestiCoullInterval(int, int, double) - Static method in class org.apache.commons.math4.legacy.stat.interval.IntervalUtils: Create an Agresti-Coull binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
getAllDerivatives() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get all partial derivatives.
getArgument() - Method in exception org.apache.commons.math4.legacy.exception.MathIllegalNumberException
getArity() - Method in class org.apache.commons.math4.legacy.genetics.TournamentSelection: Gets the arity (number of chromosomes drawn to the tournament).
getAvailableLocales() - Static method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the set of locales for which real vectors formats are available.
getAvailableLocales() - Static method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Get the set of locales for which real vectors formats are available.
getAvailableLocales() - Static method in class org.apache.commons.math4.legacy.util.ComplexFormat: Get the set of locales for which complex formats are available.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in interface org.apache.commons.math4.legacy.ode.nonstiff.FieldButcherArrayProvider: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Get the external weights for the high order method from Butcher array.
getBinCount() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns the number of bins.
getBinStats() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns a copy of the SummaryStatistics instances containing statistics describing the values in each of the bins.
getBoundIsAllowed() - Method in exception org.apache.commons.math4.legacy.exception.NumberIsTooLargeException
getBoundIsAllowed() - Method in exception org.apache.commons.math4.legacy.exception.NumberIsTooSmallException
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in interface org.apache.commons.math4.legacy.ode.nonstiff.FieldButcherArrayProvider: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getCenters() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Returns a copy of the centers array.
getCheck() - Method in class org.apache.commons.math4.legacy.linear.ConjugateGradient: Returns true if positive-definiteness should be checked for both matrix and preconditioner.
getCheck() - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns true if symmetry of the matrix, and symmetry as well as positive definiteness of the preconditioner should be checked.
getChiSquare() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get the sum of the squares of the residuals.
getChiSquare() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the sum of the squares of the residuals.
getChromosomeList() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Access the list of chromosomes.
getChromosomes() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Returns an unmodifiable list of the chromosomes in this population.
getClopperPearsonInterval(int, int, double) - Static method in class org.apache.commons.math4.legacy.stat.interval.IntervalUtils: Create a Clopper-Pearson binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
getClusters() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns the list of clusters resulting from the last call to FuzzyKMeansClusterer.cluster(Collection).
getCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver
getCoefficients() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraint: Gets the coefficients of the constraint (left hand side).
getCoefficients() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction: Gets the coefficients of the linear equation being optimized.
getColumn() - Method in exception org.apache.commons.math4.legacy.linear.NonPositiveDefiniteMatrixException
getColumn() - Method in exception org.apache.commons.math4.legacy.linear.NonSymmetricMatrixException
getColumn() - Method in class org.apache.commons.math4.neuralnet.twod.util.LocationFinder.Location
getColumn(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the entries in column number col as an array.
getColumn(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entries at the given column index as an array.
getColumn(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Get the entries in column number col as an array.
getColumn(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entries at the given column index as an array.
getColumn(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get the entries in column number col as an array.
getColumn(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entries at the given column index as an array.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Gets the number of columns.
getColumnDimension() - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Gets the number of columns.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Gets the number of columns.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Gets the number of columns.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.JacobiPreconditioner: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.RealLinearOperator: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Gets the number of columns.
getColumnMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the entries in column number column as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entries at the given column index as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Get the entries in column number column as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entries at the given column index as a column matrix.
getColumnMatrix(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get the entries in column number column as a column matrix.
getColumnMatrix(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entries at the given column index as a column matrix.
getColumnSeparator() - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the format separator between components.
getColumnVector(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the entries in column number column as a vector.
getColumnVector(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entries at the given column index as a vector.
getColumnVector(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns the entries in column number column as a vector.
getColumnVector(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entries at the given column index as a vector.
getColumnVector(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the entries in column number column as a vector.
getColumnVector(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entries at the given column index as a vector.
getCompiler(int, int) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Get the compiler for number of free parameters and order.
getCompleteState() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get the complete current state.
getComponents() - Method in class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution: Gets the distributions that make up the mixture model.
getConditionNumber() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Return the condition number of the matrix.
getConfidenceLevel() - Method in class org.apache.commons.math4.legacy.stat.interval.ConfidenceInterval
getConstantTerm() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction: Gets the constant of the linear equation being optimized.
getConstraints() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraintSet: Gets the set of linear constraints.
getConstraints() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearOptimizer
getContext() - Method in exception org.apache.commons.math4.legacy.exception.MathRuntimeException: Gets a reference to the "rich context" data structure that allows to customize error messages and store key, value pairs in exceptions.
getContext() - Method in exception org.apache.commons.math4.legacy.exception.NullArgumentException: Gets a reference to the "rich context" data structure that allows to customize error messages and store key, value pairs in exceptions.
getContext() - Method in interface org.apache.commons.math4.legacy.exception.util.ExceptionContextProvider: Gets a reference to the "rich context" data structure that allows to customize error messages and store key, value pairs in exceptions.
getControlMatrix() - Method in class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Returns the control matrix.
getControlMatrix() - Method in interface org.apache.commons.math4.legacy.filter.ProcessModel: Returns the control matrix.
getConvergence() - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Get the convergence threshold for event localization.
getConvergence() - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Get the convergence threshold for event localization.
getConvergenceChecker() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Gets the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math4.legacy.optim.AbstractOptimizationProblem: Gets the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Gets the convergence checker.
getConvergenceChecker() - Method in interface org.apache.commons.math4.legacy.optim.OptimizationProblem: Gets the convergence checker.
getCoolingSchedule() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing
getCorrelationMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Returns the correlation matrix.
getCorrelationMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Returns the correlation matrix.
getCorrelationMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Calculate the Spearman Rank Correlation Matrix.
getCorrelationPValues() - Method in class org.apache.commons.math4.legacy.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.math4.legacy.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)
getCost() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get the cost.
getCost() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the cost.
getCostRelativeTolerance() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Gets the value of a tuning parameter.
getCount() - Method in class org.apache.commons.math4.legacy.core.IntegerSequence.Incrementor: Gets the current count.
getCount(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the number of values equal to v.
getCounter() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the evaluations counter.
getCovariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the covariance matrix of the values that have been added.
getCovariance() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns the covariance of the available values.
getCovariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the covariance matrix of the values that have been added.
getCovariance(double) - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the n × n covariance matrix.
getCovariance(int, int) - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Get the covariance for an individual element of the covariance matrix.
getCovarianceMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Returns the covariance matrix.
getCovarianceMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Returns the covariance matrix.
getCovarianceOfParameters(int, int) - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the covariance between regression parameters i and j.
getCovariances() - Method in class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Gets the covariance matrix.
getCovariances(double) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get the covariance matrix of the optimized parameters.
getCovariances(double) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the covariance matrix of the optimized parameters.
getCrossoverPoints() - Method in class org.apache.commons.math4.legacy.genetics.NPointCrossover: Returns the number of crossover points used by this CrossoverPolicy.
getCrossoverPolicy() - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the crossover policy.
getCrossoverRate() - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the crossover rate.
getCumFreq(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the cumulative frequency of values less than or equal to v.
getCumPct(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCurrentMainSetJacobian(double[][]) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Get the current value of the Jacobian matrix with respect to state.
getCurrentParameterJacobian(String, double[]) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Get the current value of the Jacobian matrix with respect to one parameter.
getCurrentSignedStepsize() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the current signed value of the integration stepsize.
getCurrentSignedStepsize() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the current signed value of the integration stepsize.
getCurrentSignedStepsize() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get the current signed value of the integration stepsize.
getCurrentSignedStepsize() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get the current signed value of the integration stepsize.
getCurrentState() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Get the state at current grid point time.
getCurrentState() - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldStepInterpolator: Get the state at current grid point time.
getCurrentStepStart() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the current value of the step start time t_i.
getCurrentStepStart() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the current value of the step start time t_i.
getCurrentStepStart() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get the current value of the step start time t_i.
getCurrentStepStart() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Get the current value of the step start time t_i.
getCurrentStepStart() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get the current value of the step start time t_i.
getCurrentTime() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the current soft grid point time.
getCurrentTime() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Get the current grid point time.
getD() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets the block diagonal matrix D of the decomposition.
getData() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Return the covariance matrix as two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Get a copy of the stored data array.
getDataPoints() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns an unmodifiable list of the data points used in the last call to FuzzyKMeansClusterer.cluster(Collection).
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Get a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Get a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Returns a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Get a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Gets a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Get a reference to the stored data array.
getDecimalDigits() - Method in class org.apache.commons.math4.legacy.core.dfp.DfpDec: Get the number of decimal digits this class is going to represent.
getDecomposition() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer: Get the matrix decomposition algorithm used to solve the normal equations.
getDefaultNumberFormat() - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Create a default number format.
getDefaultNumberFormat(Locale) - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Create a default number format.
getDerivative() - Method in class org.apache.commons.math4.legacy.ode.FieldODEStateAndDerivative: Get derivative of the main state at time.
getDerivative(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Get the derivative with respect to a particular index variable.
getDeterminant() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition: Return the determinant of the matrix.
getDeterminant() - Method in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Return the determinant of the matrix.
getDeterminant() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Computes the determinant of the matrix.
getDeterminant() - Method in class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Return the determinant of the matrix.
getDeterminant() - Method in class org.apache.commons.math4.legacy.linear.LUDecomposition: Return the determinant of the matrix.
getDiagonalOfHatMatrix(double[]) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Gets the diagonal of the Hat matrix also known as the leverage matrix.
getDimension() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Get the space dimensionality.
getDimension() - Method in class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution: Gets the number of random variables of the distribution.
getDimension() - Method in interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution: Gets the number of random variables of the distribution.
getDimension() - Method in exception org.apache.commons.math4.legacy.exception.DimensionMismatchException
getDimension() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns the size of the vector.
getDimension() - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.ode.EquationsMapper: Get the dimension of the secondary state parameters.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.FieldSecondaryEquations: Get the dimension of the secondary state parameters.
getDimension() - Method in class org.apache.commons.math4.legacy.ode.FirstOrderConverter: Get the dimension of the problem.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderDifferentialEquations: Get the dimension of the problem.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldDifferentialEquations: Get the dimension of the problem.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.SecondaryEquations: Get the dimension of the secondary state parameters.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.SecondOrderDifferentialEquations: Get the dimension of the problem.
getDimension() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Returns the space dimension.
getDimension() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the dimension of the data.
getDimension() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns the dimension of the data.
getDimension() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the dimension of the data.
getDistance(OpenMapRealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Optimized method to compute distance.
getDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Distance between two vectors.
getDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Distance between two vectors.
getDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Distance between two vectors.
getDistanceMeasure() - Method in class org.apache.commons.math4.legacy.ml.clustering.Clusterer: Returns the DistanceMeasure instance used by this clusterer.
getE() - Method in class org.apache.commons.math4.legacy.core.dfp.DfpField: Get the constant e.
getEigenvector(int) - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets a copy of the i^th eigenvector of the original matrix.
getElement(int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the element at the specified index.
getElement(int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns the element at the specified index.
getElitismRate() - Method in class org.apache.commons.math4.legacy.genetics.ElitisticListPopulation: Access the elitism rate.
getEndProbability() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Returns the entry in the specified index.
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Return the entry at the specified index.
getEntry(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Returns the entry in the specified index.
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Return the entry at the specified index.
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Return the entry at the specified index.
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Returns the entry in the specified index.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Get the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns the entry in the specified row and column.