- ABS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- abs() - Method in class org.apache.commons.math.complex.Complex
-
Return the absolute value of this complex number.
- abs() - Method in class org.apache.commons.math.fraction.BigFraction
-
- abs() - Method in class org.apache.commons.math.fraction.Fraction
-
Returns the absolute value of this fraction.
- abs(int) - Static method in class org.apache.commons.math.util.FastMath
-
Absolute value.
- abs(long) - Static method in class org.apache.commons.math.util.FastMath
-
Absolute value.
- abs(float) - Static method in class org.apache.commons.math.util.FastMath
-
Absolute value.
- abs(double) - Static method in class org.apache.commons.math.util.FastMath
-
Absolute value.
- absoluteAccuracy - Variable in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Maximum absolute error.
- AbstractContinuousDistribution - Class in org.apache.commons.math.distribution
-
Base class for continuous distributions.
- AbstractContinuousDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Default constructor.
- AbstractDistribution - Class in org.apache.commons.math.distribution
-
Base class for probability distributions.
- AbstractDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractDistribution
-
Default constructor.
- AbstractEstimator - Class in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- AbstractEstimator() - Constructor for class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Build an abstract estimator for least squares problems.
- AbstractFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
Basic implementation of
FieldMatrix
methods regardless of the underlying storage.
- AbstractFieldMatrix() - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
-
Constructor for use with Serializable
- AbstractFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
-
Creates a matrix with no data
- AbstractFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.AbstractFieldMatrix
-
Create a new FieldMatrix with the supplied row and column dimensions.
- AbstractFormat - Class in org.apache.commons.math.fraction
-
- AbstractFormat() - Constructor for class org.apache.commons.math.fraction.AbstractFormat
-
Create an improper formatting instance with the default number format
for the numerator and denominator.
- AbstractFormat(NumberFormat) - Constructor for class org.apache.commons.math.fraction.AbstractFormat
-
Create an improper formatting instance with a custom number format for
both the numerator and denominator.
- AbstractFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.fraction.AbstractFormat
-
Create an improper formatting instance with a custom number format for
the numerator and a custom number format for the denominator.
- AbstractIntegerDistribution - Class in org.apache.commons.math.distribution
-
Base class for integer-valued discrete distributions.
- AbstractIntegerDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Default constructor.
- AbstractIntegrator - Class in org.apache.commons.math.ode
-
Base class managing common boilerplate for all integrators.
- AbstractIntegrator(String) - Constructor for class org.apache.commons.math.ode.AbstractIntegrator
-
Build an instance.
- AbstractIntegrator() - Constructor for class org.apache.commons.math.ode.AbstractIntegrator
-
Build an instance with a null name.
- AbstractLeastSquaresOptimizer - Class in org.apache.commons.math.optimization.general
-
Base class for implementing least squares optimizers.
- AbstractLeastSquaresOptimizer() - Constructor for class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Simple constructor with default settings.
- AbstractLinearOptimizer - Class in org.apache.commons.math.optimization.linear
-
Base class for implementing linear optimizers.
- AbstractLinearOptimizer() - Constructor for class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Simple constructor with default settings.
- AbstractListChromosome<T> - Class in org.apache.commons.math.genetics
-
Chromosome represented by an immutable list of a fixed length.
- AbstractListChromosome(List<T>) - Constructor for class org.apache.commons.math.genetics.AbstractListChromosome
-
Constructor.
- AbstractListChromosome(T[]) - Constructor for class org.apache.commons.math.genetics.AbstractListChromosome
-
Constructor.
- AbstractMultipleLinearRegression - Class in org.apache.commons.math.stat.regression
-
Abstract base class for implementations of MultipleLinearRegression.
- AbstractMultipleLinearRegression() - Constructor for class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
- AbstractRandomGenerator - Class in org.apache.commons.math.random
-
- AbstractRandomGenerator() - Constructor for class org.apache.commons.math.random.AbstractRandomGenerator
-
Construct a RandomGenerator.
- AbstractRealMatrix - Class in org.apache.commons.math.linear
-
Basic implementation of RealMatrix methods regardless of the underlying storage.
- AbstractRealMatrix() - Constructor for class org.apache.commons.math.linear.AbstractRealMatrix
-
Creates a matrix with no data
- AbstractRealMatrix(int, int) - Constructor for class org.apache.commons.math.linear.AbstractRealMatrix
-
Create a new RealMatrix with the supplied row and column dimensions.
- AbstractRealVector - Class in org.apache.commons.math.linear
-
This class provides default basic implementations for many methods in the
RealVector
interface.
- AbstractRealVector() - Constructor for class org.apache.commons.math.linear.AbstractRealVector
-
- AbstractRealVector.EntryImpl - Class in org.apache.commons.math.linear
-
An entry in the vector.
- AbstractRealVector.EntryImpl() - Constructor for class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
-
Simple constructor.
- AbstractRealVector.SparseEntryIterator - Class in org.apache.commons.math.linear
-
This class should rare be used, but is here to provide
a default implementation of sparseIterator(), which is implemented
by walking over the entries, skipping those whose values are the default one.
- AbstractRealVector.SparseEntryIterator() - Constructor for class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
-
Simple constructor.
- AbstractScalarDifferentiableOptimizer - Class in org.apache.commons.math.optimization.general
-
Base class for implementing optimizers for multivariate scalar functions.
- AbstractScalarDifferentiableOptimizer() - Constructor for class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Simple constructor with default settings.
- AbstractStepInterpolator - Class in org.apache.commons.math.ode.sampling
-
This abstract class represents an interpolator over the last step
during an ODE integration.
- AbstractStepInterpolator() - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Simple constructor.
- AbstractStepInterpolator(double[], boolean) - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Simple constructor.
- AbstractStepInterpolator(AbstractStepInterpolator) - Constructor for class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Copy constructor.
- AbstractStorelessUnivariateStatistic - Class in org.apache.commons.math.stat.descriptive
-
- AbstractStorelessUnivariateStatistic() - Constructor for class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
- AbstractUnivariateRealOptimizer - Class in org.apache.commons.math.optimization.univariate
-
Provide a default implementation for several functions useful to generic
optimizers.
- AbstractUnivariateRealOptimizer(int, double) - Constructor for class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Deprecated.
in 2.2. Please use the "setter" methods to assign meaningful
values to the maximum numbers of iterations and evaluations, and to the
absolute and relative accuracy thresholds.
- AbstractUnivariateRealOptimizer() - Constructor for class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Default constructor.
- AbstractUnivariateStatistic - Class in org.apache.commons.math.stat.descriptive
-
- AbstractUnivariateStatistic() - Constructor for class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
- AbstractWell - Class in org.apache.commons.math.random
-
This abstract class implements the WELL class of pseudo-random number generator
from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
- AbstractWell(int, int, int, int) - Constructor for class org.apache.commons.math.random.AbstractWell
-
Creates a new random number generator.
- AbstractWell(int, int, int, int, int) - Constructor for class org.apache.commons.math.random.AbstractWell
-
Creates a new random number generator using a single int seed.
- AbstractWell(int, int, int, int, int[]) - Constructor for class org.apache.commons.math.random.AbstractWell
-
Creates a new random number generator using an int array seed.
- AbstractWell(int, int, int, int, long) - Constructor for class org.apache.commons.math.random.AbstractWell
-
Creates a new random number generator using a single long seed.
- acceptStep(AbstractStepInterpolator, double[], double[], double) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Accept a step, triggering events and step handlers.
- ACOS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- acos() - Method in class org.apache.commons.math.complex.Complex
-
- acos(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the arc-cosine of the argument.
- acos(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the arc cosine of a number.
- acosh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the inverse hyperbolic cosine of a number.
- AdamsBashforthIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements explicit Adams-Bashforth integrators for Ordinary
Differential Equations.
- AdamsBashforthIntegrator(int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
-
Build an Adams-Bashforth integrator with the given order and step control parameters.
- AdamsBashforthIntegrator(int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsBashforthIntegrator
-
Build an Adams-Bashforth integrator with the given order and step control parameters.
- AdamsIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
- AdamsIntegrator(String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
-
Build an Adams integrator with the given order and step control prameters.
- AdamsIntegrator(String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsIntegrator
-
Build an Adams integrator with the given order and step control parameters.
- AdamsMoultonIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements implicit Adams-Moulton integrators for Ordinary
Differential Equations.
- AdamsMoultonIntegrator(int, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
-
Build an Adams-Moulton integrator with the given order and error control parameters.
- AdamsMoultonIntegrator(int, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdamsMoultonIntegrator
-
Build an Adams-Moulton integrator with the given order and error control parameters.
- AdamsNordsieckTransformer - Class in org.apache.commons.math.ode.nonstiff
-
Transformer to Nordsieck vectors for Adams integrators.
- AdaptiveStepsizeIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This abstract class holds the common part of all adaptive
stepsize integrators for Ordinary Differential Equations.
- AdaptiveStepsizeIntegrator(String, double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Build an integrator with the given stepsize bounds.
- AdaptiveStepsizeIntegrator(String, double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Build an integrator with the given stepsize bounds.
- ADD - Static variable in class org.apache.commons.math.analysis.BinaryFunction
-
Deprecated.
- add(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function adding the instance and another function.
- add(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function adding a constant term to the instance.
- add(PolynomialFunction) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Add a polynomial to the instance.
- add(Complex) - Method in class org.apache.commons.math.complex.Complex
-
Return the sum of this complex number and the given complex number.
- add(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Add x to this.
- add(T) - Method in interface org.apache.commons.math.FieldElement
-
Compute this + a.
- add(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
-
Adds the value of this fraction to the passed
BigInteger
,
returning the result in reduced form.
- add(int) - Method in class org.apache.commons.math.fraction.BigFraction
-
Adds the value of this fraction to the passed integer, returning
the result in reduced form.
- add(long) - Method in class org.apache.commons.math.fraction.BigFraction
-
Adds the value of this fraction to the passed long, returning
the result in reduced form.
- add(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
-
Adds the value of this fraction to another, returning the result in
reduced form.
- add(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
-
Adds the value of this fraction to another, returning the result in reduced form.
- add(int) - Method in class org.apache.commons.math.fraction.Fraction
-
Add an integer to the fraction.
- add(Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
-
Add a vector to the instance.
- add(double, Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
-
Add a scaled vector to the instance.
- add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Compute the sum of this and m.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Compute the sum of this and m.
- add(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Compute the sum of this vector and v
.
- add(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Compute the sum of this vector and v
.
- add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Compute the sum of this and m.
- add(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Compute the sum of this and m
.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Compute the sum of this and m.
- add(Array2DRowRealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Compute the sum of this and m
.
- add(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute the sum of this and v.
- add(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute the sum of this and v.
- add(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute the sum of this and v.
- add(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Compute the sum of this vector and v
.
- add(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Compute the sum of this vector and v
.
- add(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Compute the sum of this and v.
- add(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Compute the sum of this and m.
- add(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Compute the sum of this and m
.
- add(BigMatrixImpl) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Compute the sum of this and m
.
- add(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Compute the sum of this and m.
- add(BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Compute the sum of this and m
.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Compute the sum of this and m.
- add(BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Compute the sum of this and m
.
- add(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Compute the sum of this and m.
- add(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Compute the sum of this and v.
- add(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Compute the sum of this and v.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute the sum of this and m.
- add(OpenMapRealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute the sum of this and m
.
- add(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Compute the sum of this vector and v
.
- add(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to add two OpenMapRealVectors.
- add(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Compute the sum of this and m.
- add(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Compute the sum of this and m.
- add(RealMatrixImpl) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Compute the sum of this and m
.
- add(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Compute the sum of this vector and v
.
- add(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Compute the sum of this vector and v
.
- add(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Optimized method to add sparse vectors.
- add(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Compute the sum of this and v.
- add(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Compute the sum of this and v.
- add(BigReal) - Method in class org.apache.commons.math.util.BigReal
-
Compute this + a.
- addAndCheck(int, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Add two integers, checking for overflow.
- addAndCheck(long, long) - Static method in class org.apache.commons.math.util.MathUtils
-
Add two long integers, checking for overflow.
- addChromosome(Chromosome) - Method in class org.apache.commons.math.genetics.ListPopulation
-
Add the given chromosome to the population.
- addChromosome(Chromosome) - Method in interface org.apache.commons.math.genetics.Population
-
Add the given chromosome to the population.
- addData(double, double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Adds the observation (x,y) to the regression data set.
- addData(double[][]) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Adds the observations represented by the elements in
data
.
- addElement(double) - Method in interface org.apache.commons.math.util.DoubleArray
-
Adds an element to the end of this expandable array
- addElement(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Adds an element to the end of this expandable array.
- addElementRolling(double) - Method in interface org.apache.commons.math.util.DoubleArray
-
Adds an element to the end of the array and removes the first
element in the array.
- addElementRolling(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Adds an element to the end of the array and removes the first
element in the array.
- addElements(double[]) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Adds several element to the end of this expandable array.
- addEndTimeChecker(double, double, CombinedEventsManager) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Deprecated.
as of 2.2, this method is not used any more
- addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Add an event handler to the integrator.
- addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Add an events handler.
- addEventHandler(EventHandlerWithJacobians, double, double, int) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Add an event handler to the integrator.
- addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Add an event handler to the integrator.
- addEventHandler(EventHandler, double, double, int) - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Add an event handler to the integrator.
- ADDITIVE_MODE - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
-
additive expansion mode
- addMeasurement(WeightedMeasurement) - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Add a new measurement to the set.
- addObservedPoint(double, double) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Add an observed (x,y) point to the sample with unit weight.
- addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Add an observed weighted (x,y) point to the sample.
- addObservedPoint(WeightedObservedPoint) - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Add an observed weighted (x,y) point to the sample.
- addObservedPoint(double, double) - Method in class org.apache.commons.math.optimization.fitting.GaussianFitter
-
Adds point (x
, y
) to list of observed points
with a weight of 1.0.
- addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.GaussianFitter
-
Adds point (x
, y
) to list of observed points
with a weight of weight
.
- addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.HarmonicFitter
-
Add an observed weighted (x,y) point to the sample.
- addObservedPoint(double, double, double) - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter
-
Add an observed weighted (x,y) point to the sample.
- addParameter(EstimatedParameter) - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Add a parameter to the problem.
- addPoint(T) - Method in class org.apache.commons.math.stat.clustering.Cluster
-
Add a point to this cluster.
- addStepHandler(StepHandler) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Add a step handler to this integrator.
- addStepHandler(StepHandlerWithJacobians) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Add a step handler to this integrator.
- addStepHandler(StepHandler) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Add a step handler to this integrator.
- addStepHandler(StepHandler) - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Add a step handler to this integrator.
- addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Change an entry in the specified row and column.
- addToEntry(int, int, double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Change an entry in the specified row and column.
- addToEntry(int, int, T) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Change an entry in the specified row and column.
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Adds the value to the dataset.
- addValue(double[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Add an n-tuple to the data
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Add a value to the data
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Adds the value to the dataset.
- addValue(double[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Add an n-tuple to the data
- addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Add a value to the data
- addValue(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- addValue(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Adds 1 to the frequency count for v.
- addValue(int) - Method in class org.apache.commons.math.stat.Frequency
-
Adds 1 to the frequency count for v.
- addValue(Integer) - Method in class org.apache.commons.math.stat.Frequency
-
Deprecated.
to be removed in math 3.0
- addValue(long) - Method in class org.apache.commons.math.stat.Frequency
-
Adds 1 to the frequency count for v.
- addValue(char) - Method in class org.apache.commons.math.stat.Frequency
-
Adds 1 to the frequency count for v.
- advance(AbstractRealVector.EntryImpl) - Method in class org.apache.commons.math.linear.AbstractRealVector.SparseEntryIterator
-
Advance an entry up to the next nonzero one.
- advance() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator
-
Advance iterator one step further.
- advance() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap.Iterator
-
Advance iterator one step further.
- aggregate(Collection<SummaryStatistics>) - Static method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Computes aggregate summary statistics.
- AggregateSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
An aggregator for SummaryStatistics
from several data sets or
data set partitions.
- AggregateSummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Initializes a new AggregateSummaryStatistics with default statistics
implementations.
- AggregateSummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Initializes a new AggregateSummaryStatistics with the specified statistics
object as a prototype for contributing statistics and for the internal
aggregate statistics.
- AggregateSummaryStatistics(SummaryStatistics, SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Initializes a new AggregateSummaryStatistics with the specified statistics
object as a prototype for contributing statistics and for the internal
aggregate statistics.
- align(int) - Method in class org.apache.commons.math.dfp.Dfp
-
Make our exp equal to the supplied one, this may cause rounding.
- angle(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
-
Compute the angular separation between two vectors.
- anovaFValue(Collection<double[]>) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
-
Computes the ANOVA F-value for a collection of double[]
arrays.
- anovaFValue(Collection<double[]>) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
-
Computes the ANOVA F-value for a collection of double[]
arrays.
- anovaPValue(Collection<double[]>) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
-
Computes the ANOVA P-value for a collection of double[]
arrays.
- anovaPValue(Collection<double[]>) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
-
Computes the ANOVA P-value for a collection of double[]
arrays.
- anovaTest(Collection<double[]>, double) - Method in interface org.apache.commons.math.stat.inference.OneWayAnova
-
Performs an ANOVA test, evaluating the null hypothesis that there
is no difference among the means of the data categories.
- anovaTest(Collection<double[]>, double) - Method in class org.apache.commons.math.stat.inference.OneWayAnovaImpl
-
Performs an ANOVA test, evaluating the null hypothesis that there
is no difference among the means of the data categories.
- AnyMatrix - Interface in org.apache.commons.math.linear
-
Interface defining very basic matrix operations.
- append(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending a vector to this vector.
- append(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending a vector to this vector.
- append(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending a T to this vector.
- append(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending a T array to this vector.
- append(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending a vector to this vector.
- append(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending a vector to this vector.
- append(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending a double to this vector.
- append(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending a double array to this vector.
- append(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Construct a vector by appending a vector to this vector.
- append(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Construct a vector by appending a T to this vector.
- append(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Construct a vector by appending a T array to this vector.
- append(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to append a OpenMapRealVector.
- append(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Construct a vector by appending a vector to this vector.
- append(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Construct a vector by appending a double to this vector.
- append(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Construct a vector by appending a double array to this vector.
- append(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Construct a vector by appending a vector to this vector.
- append(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Construct a vector by appending a double to this vector.
- append(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Construct a vector by appending a double array to this vector.
- append(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Construct a vector by appending a vector to this vector.
- append(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Construct a vector by appending a vector to this vector.
- append(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Construct a vector by appending a T to this vector.
- append(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Construct a vector by appending a T array to this vector.
- append(ContinuousOutputModel) - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Append another model at the end of the instance.
- apply(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Apply the given statistic to the data associated with this set of statistics.
- apply(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Apply the given statistic to the data associated with this set of statistics.
- applyInverseTo(Vector3D) - Method in class org.apache.commons.math.geometry.Rotation
-
Apply the inverse of the rotation to a vector.
- applyInverseTo(Rotation) - Method in class org.apache.commons.math.geometry.Rotation
-
Apply the inverse of the instance to another rotation.
- applyTo(Vector3D) - Method in class org.apache.commons.math.geometry.Rotation
-
Apply the rotation to a vector.
- applyTo(Rotation) - Method in class org.apache.commons.math.geometry.Rotation
-
Apply the instance to another rotation.
- ArgumentOutsideDomainException - Exception in org.apache.commons.math
-
Error thrown when a method is called with an out of bounds argument.
- ArgumentOutsideDomainException(double, double, double) - Constructor for exception org.apache.commons.math.ArgumentOutsideDomainException
-
Constructs an exception with specified formatted detail message.
- ArgUtils - Class in org.apache.commons.math.exception.util
-
Utility class for transforming the list of arguments passed to
constructors of exceptions.
- Array2DRowFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
Implementation of FieldMatrix
using a FieldElement
[][] array to store entries.
- Array2DRowFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Creates a matrix with no data
- Array2DRowFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new FieldMatrix with the supplied row and column dimensions.
- Array2DRowFieldMatrix(T[][]) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new FieldMatrix using the input array as the underlying
data array.
- Array2DRowFieldMatrix(T[][], boolean) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new FieldMatrix using the input array as the underlying
data array.
- Array2DRowFieldMatrix(T[]) - Constructor for class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new (column) FieldMatrix using v
as the
data for the unique column of the v.length x 1
matrix
created.
- Array2DRowRealMatrix - Class in org.apache.commons.math.linear
-
Implementation of RealMatrix using a double[][] array to store entries and
LU decomposition to support linear system
solution and inverse.
- Array2DRowRealMatrix() - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Creates a matrix with no data
- Array2DRowRealMatrix(int, int) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new RealMatrix with the supplied row and column dimensions.
- Array2DRowRealMatrix(double[][]) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new RealMatrix using the input array as the underlying
data array.
- Array2DRowRealMatrix(double[][], boolean) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new RealMatrix using the input array as the underlying
data array.
- Array2DRowRealMatrix(double[]) - Constructor for class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new (column) RealMatrix using v
as the
data for the unique column of the v.length x 1
matrix
created.
- ArrayFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
- ArrayFieldVector(Field<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Build a 0-length vector.
- ArrayFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a (size)-length vector of zeros.
- ArrayFieldVector(int, T) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct an (size)-length vector with preset values.
- ArrayFieldVector(T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from an array, copying the input array.
- ArrayFieldVector(Field<T>, T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from an array, copying the input array.
- ArrayFieldVector(T[], boolean) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Create a new ArrayFieldVector using the input array as the underlying
data array.
- ArrayFieldVector(Field<T>, T[], boolean) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Create a new ArrayFieldVector using the input array as the underlying
data array.
- ArrayFieldVector(T[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from part of a array.
- ArrayFieldVector(FieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from another vector, using a deep copy.
- ArrayFieldVector(ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from another vector, using a deep copy.
- ArrayFieldVector(ArrayFieldVector<T>, boolean) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector from another vector.
- ArrayFieldVector(ArrayFieldVector<T>, ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayFieldVector(ArrayFieldVector<T>, T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayFieldVector(T[], ArrayFieldVector<T>) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayFieldVector(T[], T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayFieldVector(Field<T>, T[], T[]) - Constructor for class org.apache.commons.math.linear.ArrayFieldVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector - Class in org.apache.commons.math.linear
-
This class implements the
RealVector
interface with a double array.
- ArrayRealVector() - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Build a 0-length vector.
- ArrayRealVector(int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a (size)-length vector of zeros.
- ArrayRealVector(int, double) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct an (size)-length vector with preset values.
- ArrayRealVector(double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from an array, copying the input array.
- ArrayRealVector(double[], boolean) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Create a new ArrayRealVector using the input array as the underlying
data array.
- ArrayRealVector(double[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from part of a array.
- ArrayRealVector(Double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from an array.
- ArrayRealVector(Double[], int, int) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from part of a Double array
- ArrayRealVector(RealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from another vector, using a deep copy.
- ArrayRealVector(ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from another vector, using a deep copy.
- ArrayRealVector(ArrayRealVector, boolean) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector from another vector.
- ArrayRealVector(ArrayRealVector, ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(ArrayRealVector, RealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(RealVector, ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(ArrayRealVector, double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(double[], ArrayRealVector) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- ArrayRealVector(double[], double[]) - Constructor for class org.apache.commons.math.linear.ArrayRealVector
-
Construct a vector by appending one vector to another vector.
- asCollector(BivariateRealFunction, double) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Generates a function that iteratively apply instance function on all
elements of an array.
- asCollector(BivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Generates a function that iteratively apply instance function on all
elements of an array.
- asCollector(double) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Generates a function that iteratively apply instance function on all
elements of an array.
- asCollector() - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Generates a function that iteratively apply instance function on all
elements of an array.
- ASIN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- asin() - Method in class org.apache.commons.math.complex.Complex
-
- asin(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the arc-sine of the argument.
- asin(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the arc sine of a number.
- asinh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the inverse hyperbolic sine of a number.
- ATAN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- atan() - Method in class org.apache.commons.math.complex.Complex
-
- atan(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the arc tangent of the argument
Uses the typical taylor series
but may reduce arguments using the following identity
tan(x+y) = (tan(x) + tan(y)) / (1 - tan(x)*tan(y))
since tan(PI/8) = sqrt(2)-1,
atan(x) = atan( (x - sqrt(2) + 1) / (1+x*sqrt(2) - x) + PI/8.0
- atan(double) - Static method in class org.apache.commons.math.util.FastMath
-
Arctangent function
- ATAN2 - Static variable in class org.apache.commons.math.analysis.BinaryFunction
-
Deprecated.
- atan2(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Two arguments arctangent function
- atanh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the inverse hyperbolic tangent of a number.
- atanInternal(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the arc-tangent of the argument.
- calculateAdjustedRSquared() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Returns the adjusted R-squared statistic, defined by the formula
- calculateBeta() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the beta of multiple linear regression in matrix notation.
- calculateBeta() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Calculates beta by GLS.
- calculateBeta() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Calculates the regression coefficients using OLS.
- calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the beta variance of multiple linear regression in matrix
notation.
- calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Calculates the variance on the beta.
- calculateBetaVariance() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Calculates the variance-covariance matrix of the regression parameters.
- calculateErrorVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the variance of the error term.
- calculateErrorVariance() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Calculates the estimated variance of the error term using the formula
- calculateHat() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Compute the "hat" matrix.
- calculateNumericalMean() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Calculates the mean.
- calculateResiduals() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the residuals of multiple linear regression in matrix
notation.
- calculateResidualSumOfSquares() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Returns the sum of squared residuals.
- calculateRSquared() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Returns the R-Squared statistic, defined by the formula
- calculateTotalSumOfSquares() - Method in class org.apache.commons.math.stat.regression.OLSMultipleLinearRegression
-
Returns the sum of squared deviations of Y from its mean.
- calculateYVariance() - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
Calculates the variance of the y values.
- CardanEulerSingularityException - Exception in org.apache.commons.math.geometry
-
This class represents exceptions thrown while extractiong Cardan
or Euler angles from a rotation.
- CardanEulerSingularityException(boolean) - Constructor for exception org.apache.commons.math.geometry.CardanEulerSingularityException
-
Simple constructor.
- CauchyDistribution - Interface in org.apache.commons.math.distribution
-
Cauchy Distribution.
- CauchyDistributionImpl - Class in org.apache.commons.math.distribution
-
- CauchyDistributionImpl() - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Creates cauchy distribution with the medain equal to zero and scale
equal to one.
- CauchyDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Create a cauchy distribution using the given median and scale.
- CauchyDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Create a cauchy distribution using the given median and scale.
- CBRT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- cbrt(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the cubic root of a number.
- CEIL - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- ceil() - Method in class org.apache.commons.math.dfp.Dfp
-
Round to an integer using the round ceil mode.
- ceil(double) - Static method in class org.apache.commons.math.util.FastMath
-
Get the smallest whole number larger than x.
- centroidOf(Collection<T>) - Method in interface org.apache.commons.math.stat.clustering.Clusterable
-
Returns the centroid of the given Collection of points.
- centroidOf(Collection<EuclideanIntegerPoint>) - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
-
Returns the centroid of the given Collection of points.
- checkAdditionCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a matrix is addition compatible with the instance
- checkAdditionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if matrices are addition compatible
- checkColumnIndex(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a column index is valid.
- checkColumnIndex(AnyMatrix, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if a column index is valid.
- checkContractExpand(float, float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Checks the expansion factor and the contraction criteria and throws an
IllegalArgumentException if the contractionCriteria is less than the
expansionCriteria
- checker - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Convergence checker.
- checker - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Deprecated.
- checkIndex(int) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Check if an index is valid.
- checkMultiplicationCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a matrix is multiplication compatible with the instance
- checkMultiplicationCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if matrices are multiplication compatible
- checkOrder(double[], MathUtils.OrderDirection, boolean) - Static method in class org.apache.commons.math.util.MathUtils
-
Checks that the given array is sorted.
- checkOrder(double[]) - Static method in class org.apache.commons.math.util.MathUtils
-
Checks that the given array is sorted in strictly increasing order.
- checkOrder(double[], int, boolean) - Static method in class org.apache.commons.math.util.MathUtils
-
Deprecated.
as of 2.2 (please use the new checkOrder
method). To be removed in 3.0.
- checkResultComputed() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Check if a result has been computed.
- checkResultComputed() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Deprecated.
in 2.2 (no alternative).
- checkRowIndex(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a row index is valid.
- checkRowIndex(AnyMatrix, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if a row index is valid.
- checkSubMatrixIndex(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if submatrix ranges indices are valid.
- checkSubMatrixIndex(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if submatrix ranges indices are valid.
- checkSubMatrixIndex(AnyMatrix, int, int, int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if submatrix ranges indices are valid.
- checkSubMatrixIndex(AnyMatrix, int[], int[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if submatrix ranges indices are valid.
- checkSubtractionCompatible(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Check if a matrix is subtraction compatible with the instance
- checkSubtractionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Check if matrices are subtraction compatible
- checkValidity(List<T>) - Method in class org.apache.commons.math.genetics.AbstractListChromosome
-
Asserts that representation
can represent a valid chromosome.
- checkValidity(List<Integer>) - Method in class org.apache.commons.math.genetics.BinaryChromosome
-
Asserts that representation
can represent a valid chromosome.
- checkValidity(List<Double>) - Method in class org.apache.commons.math.genetics.RandomKey
-
Asserts that representation
can represent a valid chromosome.
- checkVectorDimensions(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Check if instance and specified vectors have the same dimension.
- checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Check if instance dimension is equal to some expected value.
- checkVectorDimensions(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Check if instance and specified vectors have the same dimension.
- checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Check if instance dimension is equal to some expected value.
- checkVectorDimensions(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Check if instance and specified vectors have the same dimension.
- checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Check if instance dimension is equal to some expected value.
- checkVectorDimensions(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Check if instance dimension is equal to some expected value.
- chiSquare(double[], long[]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
- chiSquare(long[][]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
- chiSquare(double[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquare(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquare(double[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquare(long[][]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareDataSetsComparison(long[], long[]) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
-
- ChiSquaredDistribution - Interface in org.apache.commons.math.distribution
-
The Chi-Squared Distribution.
- ChiSquaredDistributionImpl - Class in org.apache.commons.math.distribution
-
- ChiSquaredDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Create a Chi-Squared distribution with the given degrees of freedom.
- ChiSquaredDistributionImpl(double, GammaDistribution) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Deprecated.
as of 2.1 (to avoid possibly inconsistent state, the
"GammaDistribution" will be instantiated internally)
- ChiSquaredDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Create a Chi-Squared distribution with the given degrees of freedom and
inverse cumulative probability accuracy.
- ChiSquareTest - Interface in org.apache.commons.math.stat.inference
-
An interface for Chi-Square tests.
- chiSquareTest(double[], long[]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
- chiSquareTest(double[], long[], double) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
Performs a
Chi-square goodness of fit test evaluating the null hypothesis that the observed counts
conform to the frequency distribution described by the expected counts, with
significance level
alpha
.
- chiSquareTest(long[][]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
- chiSquareTest(long[][], double) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
-
Performs a
chi-square test of independence evaluating the null hypothesis that the classifications
represented by the counts in the columns of the input 2-way table are independent of the rows,
with significance level
alpha
.
- chiSquareTest(double[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTest(double[], long[], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Performs a
Chi-square goodness of fit test evaluating the null hypothesis that the observed counts
conform to the frequency distribution described by the expected counts, with
significance level
alpha
.
- chiSquareTest(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTest(long[][], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTest(double[], long[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTest(double[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTest(long[][], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTest(long[][]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTestDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTestDataSetsComparison(long[], long[], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
- chiSquareTestDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTestDataSetsComparison(long[], long[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
- chiSquareTestDataSetsComparison(long[], long[]) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
-
Returns the
observed significance level, or
p-value, associated with a Chi-Square two sample test comparing
bin frequency counts in
observed1
and
observed2
.
- chiSquareTestDataSetsComparison(long[], long[], double) - Method in interface org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest
-
Performs a Chi-Square two sample test comparing two binned data
sets.
- ChiSquareTestImpl - Class in org.apache.commons.math.stat.inference
-
- ChiSquareTestImpl() - Constructor for class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Construct a ChiSquareTestImpl
- ChiSquareTestImpl(ChiSquaredDistribution) - Constructor for class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Create a test instance using the given distribution for computing
inference statistics.
- CholeskyDecomposition - Interface in org.apache.commons.math.linear
-
An interface to classes that implement an algorithm to calculate the
Cholesky decomposition of a real symmetric positive-definite matrix.
- CholeskyDecompositionImpl - Class in org.apache.commons.math.linear
-
Calculates the Cholesky decomposition of a matrix.
- CholeskyDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Calculates the Cholesky decomposition of the given matrix.
- CholeskyDecompositionImpl(RealMatrix, double, double) - Constructor for class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Calculates the Cholesky decomposition of the given matrix.
- Chromosome - Class in org.apache.commons.math.genetics
-
Individual in a population.
- Chromosome() - Constructor for class org.apache.commons.math.genetics.Chromosome
-
- ChromosomePair - Class in org.apache.commons.math.genetics
-
- ChromosomePair(Chromosome, Chromosome) - Constructor for class org.apache.commons.math.genetics.ChromosomePair
-
Create a chromosome pair.
- classes() - Method in class org.apache.commons.math.util.TransformerMap
-
Returns the Set of Classes used as keys in the map.
- ClassicalRungeKuttaIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements the classical fourth order Runge-Kutta
integrator for Ordinary Differential Equations (it is the most
often used Runge-Kutta method).
- ClassicalRungeKuttaIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.ClassicalRungeKuttaIntegrator
-
Simple constructor.
- classify() - Method in class org.apache.commons.math.dfp.Dfp
-
Returns the type - one of FINITE, INFINITE, SNAN, QNAN.
- clear() - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
- clear() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Clears the internal state of the Statistic
- clear() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Clears the internal state of the Statistic
- clear() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Resets all statistics and storage
- clear() - Method in class org.apache.commons.math.stat.Frequency
-
Clears the frequency table
- clear() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Clears all data from the model.
- clear() - Method in interface org.apache.commons.math.util.DoubleArray
-
Clear the double array
- clear() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Clear the array, reset the size to the initialCapacity and the number
of elements to zero.
- clear() - Method in class org.apache.commons.math.util.TransformerMap
-
Clears all the Class to Transformer mappings.
- clearEventHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Remove all the event handlers that have been added to the integrator.
- clearEventHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Remove all the event handlers that have been added to the integrator.
- clearEventHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Remove all the event handlers that have been added to the integrator.
- clearEventsHandlers() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Remove all the events handlers that have been added to the manager.
- clearIEEEFlags() - Method in class org.apache.commons.math.dfp.DfpField
-
Clears the IEEE 854 status flags.
- clearObservations() - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Remove all observations.
- clearObservations() - Method in class org.apache.commons.math.optimization.fitting.PolynomialFitter
-
Remove all observations.
- clearResult() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Convenience function for implementations.
- clearResult() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Convenience function for implementations.
- clearResult() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Deprecated.
in 2.2 (no alternative).
- clearStepHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Remove all the step handlers that have been added to the integrator.
- clearStepHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Remove all the step handlers that have been added to the integrator.
- clearStepHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Remove all the step handlers that have been added to the integrator.
- closeReplayFile() - Method in class org.apache.commons.math.random.ValueServer
-
Closes valuesFileURL
after use in REPLAY_MODE.
- Cluster<T extends Clusterable<T>> - Class in org.apache.commons.math.stat.clustering
-
- Cluster(T) - Constructor for class org.apache.commons.math.stat.clustering.Cluster
-
Build a cluster centered at a specified point.
- cluster(Collection<T>, int, int) - Method in class org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer
-
Runs the K-means++ clustering algorithm.
- Clusterable<T> - Interface in org.apache.commons.math.stat.clustering
-
Interface for points that can be clustered together.
- cols - Variable in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Number of columns of the jacobian matrix.
- cols - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Number of columns of the jacobian matrix.
- combine(UnivariateRealFunction, BivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function combining the instance and another function.
- CombinedEventsManager - Class in org.apache.commons.math.ode.events
-
Deprecated.
as of 2.2, this class is not used anymore
- CombinedEventsManager() - Constructor for class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Simple constructor.
- comparatorPermutation(List<S>, Comparator<S>) - Static method in class org.apache.commons.math.genetics.RandomKey
-
Generates a representation of a permutation corresponding to the
data
sorted by comparator
.
- compareTo(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
-
Compares this object to another based on size.
- compareTo(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
-
Compares this object to another based on size.
- compareTo(Chromosome) - Method in class org.apache.commons.math.genetics.Chromosome
-
Compares two chromosomes based on their fitness.
- compareTo(BigReal) - Method in class org.apache.commons.math.util.BigReal
- compareTo(double, double, double) - Static method in class org.apache.commons.math.util.MathUtils
-
Compares two numbers given some amount of allowed error.
- complement(int) - Method in class org.apache.commons.math.dfp.Dfp
-
Negate the mantissa of this by computing the complement.
- Complex - Class in org.apache.commons.math.complex
-
Representation of a Complex number - a number which has both a
real and imaginary part.
- Complex(double, double) - Constructor for class org.apache.commons.math.complex.Complex
-
Create a complex number given the real and imaginary parts.
- ComplexField - Class in org.apache.commons.math.complex
-
Representation of the complex numbers field.
- ComplexFormat - Class in org.apache.commons.math.complex
-
Formats a Complex number in cartesian format "Re(c) + Im(c)i".
- ComplexFormat() - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with the default imaginary character, 'i', and the
default number format for both real and imaginary parts.
- ComplexFormat(NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom number format for both real and
imaginary parts.
- ComplexFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom number format for the real part and a
custom number format for the imaginary part.
- ComplexFormat(String) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom imaginary character, and the default
number format for both real and imaginary parts.
- ComplexFormat(String, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom imaginary character, and a custom number
format for both real and imaginary parts.
- ComplexFormat(String, NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
-
Create an instance with a custom imaginary character, a custom number
format for the real part, and a custom number format for the imaginary
part.
- ComplexUtils - Class in org.apache.commons.math.complex
-
Static implementations of common
Complex
utilities functions.
- ComposableFunction - Class in org.apache.commons.math.analysis
-
- ComposableFunction() - Constructor for class org.apache.commons.math.analysis.ComposableFunction
-
- CompositeFormat - Class in org.apache.commons.math.util
-
Base class for formatters of composite objects (complex numbers, vectors ...).
- CompositeFormat() - Constructor for class org.apache.commons.math.util.CompositeFormat
-
- computeCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Calculate the coefficients of Lagrange polynomial from the
interpolation data.
- computeCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Calculate the normal polynomial coefficients given the Newton form.
- computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Computes the correlation matrix for the columns of the
input matrix.
- computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Computes the correlation matrix for the columns of the
input rectangular array.
- computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Computes the Spearman's rank correlation matrix for the columns of the
input matrix.
- computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Computes the Spearman's rank correlation matrix for the columns of the
input rectangular array.
- computeCovarianceMatrix(RealMatrix, boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Compute a covariance matrix from a matrix whose columns represent
covariates.
- computeCovarianceMatrix(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Create a covariance matrix from a matrix whose columns represent
covariates.
- computeCovarianceMatrix(double[][], boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Compute a covariance matrix from a rectangular array whose columns represent
covariates.
- computeCovarianceMatrix(double[][]) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Create a covariance matrix from a rectangual array whose columns represent
covariates.
- computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Compute the derivatives and check the number of evaluations.
- computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math.ode.FirstOrderConverter
-
Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[]) - Method in interface org.apache.commons.math.ode.FirstOrderDifferentialEquations
-
Get the current time derivative of the state vector.
- computeDistribution() - Method in class org.apache.commons.math.random.ValueServer
-
Computes the empirical distribution using values from the file
in valuesFileURL
, using the default number of bins.
- computeDistribution(int) - Method in class org.apache.commons.math.random.ValueServer
-
Computes the empirical distribution using values from the file
in valuesFileURL
and binCount
bins.
- computeDividedDifference(double[], double[]) - Static method in class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
-
Returns a copy of the divided difference array.
- computeExp(Dfp, Dfp) - Static method in class org.apache.commons.math.dfp.DfpField
-
Compute exp(a).
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.DummyStepInterpolator
-
Compute the state at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Compute the state and derivatives at the interpolated time.
- computeJacobians(double, double[], double[], double[][], double[][]) - Method in interface org.apache.commons.math.ode.jacobians.ODEWithJacobians
-
Deprecated.
Compute the partial derivatives of ODE with respect to state.
- computeLn(Dfp, Dfp, Dfp) - Static method in class org.apache.commons.math.dfp.DfpField
-
Compute ln(a).
- computeObjectiveGradient(double[]) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Compute the gradient vector.
- computeObjectiveValue(double[]) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Compute the objective function value.
- computeObjectiveValue(UnivariateRealFunction, double) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- computeObjectiveValue(double) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Compute the objective function value.
- computeSecondDerivatives(double, double[], double[], double[]) - Method in interface org.apache.commons.math.ode.SecondOrderDifferentialEquations
-
Get the current time derivative of the state vector.
- computeStepGrowShrinkFactor(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Compute step grow/shrink factor according to normalized error.
- conjugate() - Method in class org.apache.commons.math.complex.Complex
-
Return the conjugate of this complex number.
- ConjugateGradientFormula - Enum in org.apache.commons.math.optimization.general
-
- CONSTANT_MODE - Static variable in class org.apache.commons.math.random.ValueServer
-
Always return mu
- containsClass(Class<?>) - Method in class org.apache.commons.math.util.TransformerMap
-
Tests if a Class is present in the TransformerMap.
- containsKey(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Check if a value is associated with a key.
- containsKey(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Check if a value is associated with a key.
- containsTransformer(NumberTransformer) - Method in class org.apache.commons.math.util.TransformerMap
-
Tests if a NumberTransformer is present in the TransformerMap.
- CONTINUE - Static variable in interface org.apache.commons.math.ode.events.EventHandler
-
Continue indicator.
- CONTINUE - Static variable in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
-
Deprecated.
Continue indicator.
- ContinuedFraction - Class in org.apache.commons.math.util
-
Provides a generic means to evaluate continued fractions.
- ContinuedFraction() - Constructor for class org.apache.commons.math.util.ContinuedFraction
-
Default constructor.
- ContinuousDistribution - Interface in org.apache.commons.math.distribution
-
Base interface for continuous distributions.
- ContinuousOutputModel - Class in org.apache.commons.math.ode
-
This class stores all information provided by an ODE integrator
during the integration process and build a continuous model of the
solution from this.
- ContinuousOutputModel() - Constructor for class org.apache.commons.math.ode.ContinuousOutputModel
-
Simple constructor.
- contract() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Contracts the storage array to the (size of the element set) + 1 - to
avoid a zero length array.
- contractionCriteria - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
The contraction criteria determines when the internal array will be
contracted to fit the number of elements contained in the element
array + 1.
- converged(int, RealPointValuePair, RealPointValuePair) - Method in interface org.apache.commons.math.optimization.RealConvergenceChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, RealPointValuePair, RealPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleRealPointChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, RealPointValuePair, RealPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleScalarValueChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleVectorialPointChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in class org.apache.commons.math.optimization.SimpleVectorialValueChecker
-
Check if the optimization algorithm has converged considering the last points.
- converged(int, VectorialPointValuePair, VectorialPointValuePair) - Method in interface org.apache.commons.math.optimization.VectorialConvergenceChecker
-
Check if the optimization algorithm has converged considering the last points.
- ConvergenceException - Exception in org.apache.commons.math
-
Error thrown when a numerical computation can not be performed because the
numerical result failed to converge to a finite value.
- ConvergenceException() - Constructor for exception org.apache.commons.math.ConvergenceException
-
Default constructor.
- ConvergenceException(String, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
-
- ConvergenceException(Localizable, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
-
Constructs an exception with specified formatted detail message.
- ConvergenceException(Throwable) - Constructor for exception org.apache.commons.math.ConvergenceException
-
Create an exception with a given root cause.
- ConvergenceException(Throwable, String, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
-
- ConvergenceException(Throwable, Localizable, Object...) - Constructor for exception org.apache.commons.math.ConvergenceException
-
Constructs an exception with specified formatted detail message and root cause.
- ConvergenceException - Exception in org.apache.commons.math.exception
-
Error thrown when a numerical computation can not be performed because the
numerical result failed to converge to a finite value.
- ConvergenceException() - Constructor for exception org.apache.commons.math.exception.ConvergenceException
-
Construct the exception.
- ConvergenceException(Localizable) - Constructor for exception org.apache.commons.math.exception.ConvergenceException
-
Construct the exception with a specific context.
- ConvergenceException(Localizable, Object...) - Constructor for exception org.apache.commons.math.exception.ConvergenceException
-
Construct the exception with a specific context and arguments.
- ConvergingAlgorithm - Interface in org.apache.commons.math
-
Deprecated.
in 2.2 (to be removed in 3.0). The concept of "iteration" will
be moved to a new IterativeAlgorithm
. The concept of "accuracy" is
currently is also contained in SimpleRealPointChecker
and similar classes.
- ConvergingAlgorithmImpl - Class in org.apache.commons.math
-
Deprecated.
in 2.2 (to be removed in 3.0).
- ConvergingAlgorithmImpl(int, double) - Constructor for class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
in 2.2. Derived classes should use the "setter" methods
in order to assign meaningful values to all the instances variables.
- ConvergingAlgorithmImpl() - Constructor for class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
in 2.2 (to be removed as soon as the single non-default one
has been removed).
- copy() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns a (deep) copy of this vector.
- copy() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns a (deep) copy of this vector.
- copy() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Create a new BigMatrix which is a copy of this.
- copy() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in interface org.apache.commons.math.linear.FieldVector
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Returns a (deep) copy of this vector.
- copy() - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns a (deep) copy of this.
- copy() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns a (deep) copy of this vector.
- copy() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Returns a (deep) copy of this.
- copy() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Returns a (deep) copy of this.
- copy() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Copy the instance.
- copy() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Copy the instance.
- copy() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Copy the instance.
- copy() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
Returns a copy of the statistic with the same internal state.
- copy() - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Returns a copy of the statistic with the same internal state.
- copy() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns a copy of this DescriptiveStatistics instance with the same internal state.
- copy(DescriptiveStatistics, DescriptiveStatistics) - Static method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Returns a copy of the statistic with the same internal state.
- copy(FirstMoment, FirstMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Returns a copy of the statistic with the same internal state.
- copy(FourthMoment, FourthMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns a copy of the statistic with the same internal state.
- copy(GeometricMean, GeometricMean) - Static method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Returns a copy of the statistic with the same internal state.
- copy(Kurtosis, Kurtosis) - Static method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns a copy of the statistic with the same internal state.
- copy(Mean, Mean) - Static method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Returns a copy of the statistic with the same internal state.
- copy(SecondMoment, SecondMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns a copy of the statistic with the same internal state.
- copy(SemiVariance, SemiVariance) - Static method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Returns a copy of the statistic with the same internal state.
- copy(Skewness, Skewness) - Static method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns a copy of the statistic with the same internal state.
- copy(StandardDeviation, StandardDeviation) - Static method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Returns a copy of the statistic with the same internal state.
- copy(ThirdMoment, ThirdMoment) - Static method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns a copy of the statistic with the same internal state.
- copy(Variance, Variance) - Static method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Returns a copy of the statistic with the same internal state.
- copy(Max, Max) - Static method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Returns a copy of the statistic with the same internal state.
- copy(Min, Min) - Static method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Returns a copy of the statistic with the same internal state.
- copy(Percentile, Percentile) - Static method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Copies source to dest.
- copy() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Returns a copy of the statistic with the same internal state.
- copy() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns a copy of the statistic with the same internal state.
- copy(Product, Product) - Static method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Returns a copy of the statistic with the same internal state.
- copy(Sum, Sum) - Static method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Returns a copy of the statistic with the same internal state.
- copy(SumOfLogs, SumOfLogs) - Static method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Returns a copy of the statistic with the same internal state.
- copy(SumOfSquares, SumOfSquares) - Static method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns a copy of this SummaryStatistics instance with the same internal state.
- copy(SummaryStatistics, SummaryStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns a copy of this SynchronizedDescriptiveStatistics instance with the
same internal state.
- copy(SynchronizedDescriptiveStatistics, SynchronizedDescriptiveStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Copies source to dest.
- copy() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns a copy of this SynchronizedSummaryStatistics instance with the
same internal state.
- copy(SynchronizedSummaryStatistics, SynchronizedSummaryStatistics) - Static method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Copies source to dest.
- copy() - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
-
Returns a copy of the statistic with the same internal state.
- copy(ResizableDoubleArray, ResizableDoubleArray) - Static method in class org.apache.commons.math.util.ResizableDoubleArray
-
Copies source to dest, copying the underlying data, so dest is
a new, independent copy of source.
- copy() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns a copy of the ResizableDoubleArray.
- copysign(Dfp, Dfp) - Static method in class org.apache.commons.math.dfp.Dfp
-
Creates an instance that is the same as x except that it has the sign of y.
- copySign(double, double) - Static method in class org.apache.commons.math.util.FastMath
-
Returns the first argument with the sign of the second argument.
- copySign(float, float) - Static method in class org.apache.commons.math.util.FastMath
-
Returns the first argument with the sign of the second argument.
- copySubMatrix(int, int, int, int, T[][]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Copy a submatrix.
- copySubMatrix(int[], int[], T[][]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Copy a submatrix.
- copySubMatrix(int, int, int, int, double[][]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Copy a submatrix.
- copySubMatrix(int[], int[], double[][]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Copy a submatrix.
- copySubMatrix(int, int, int, int, T[][]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Copy a submatrix.
- copySubMatrix(int[], int[], T[][]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Copy a submatrix.
- copySubMatrix(int, int, int, int, double[][]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Copy a submatrix.
- copySubMatrix(int[], int[], double[][]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Copy a submatrix.
- CorrelatedRandomVectorGenerator - Class in org.apache.commons.math.random
-
- CorrelatedRandomVectorGenerator(double[], RealMatrix, double, NormalizedRandomGenerator) - Constructor for class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Simple constructor.
- CorrelatedRandomVectorGenerator(RealMatrix, double, NormalizedRandomGenerator) - Constructor for class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Simple constructor.
- correlation(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Computes the Pearson's product-moment correlation coefficient between the two arrays.
- correlation(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Computes the Spearman's rank correlation coefficient between the two arrays.
- COS - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- cos() - Method in class org.apache.commons.math.complex.Complex
-
Compute the
cosine
of this complex number.
- cos(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the cosine of the argument.
- cos(double) - Static method in class org.apache.commons.math.util.FastMath
-
Cosine function
- COSH - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- cosh() - Method in class org.apache.commons.math.complex.Complex
-
- cosh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the hyperbolic cosine of a number.
- cosh(double) - Static method in class org.apache.commons.math.util.MathUtils
-
- cosInternal(Dfp[]) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Computes cos(a) Used when 0 < a < pi/4.
- cost - Variable in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Cost value (square root of the sum of the residuals).
- cost - Variable in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Cost value (square root of the sum of the residuals).
- Covariance - Class in org.apache.commons.math.stat.correlation
-
Computes covariances for pairs of arrays or columns of a matrix.
- Covariance() - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a Covariance with no data
- Covariance(double[][], boolean) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a Covariance matrix from a rectangular array
whose columns represent covariates.
- Covariance(double[][]) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a Covariance matrix from a rectangular array
whose columns represent covariates.
- Covariance(RealMatrix, boolean) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a covariance matrix from a matrix whose columns
represent covariates.
- Covariance(RealMatrix) - Constructor for class org.apache.commons.math.stat.correlation.Covariance
-
Create a covariance matrix from a matrix whose columns
represent covariates.
- covariance(double[], double[], boolean) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Computes the covariance between the two arrays.
- covariance(double[], double[]) - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Computes the covariance between the two arrays, using the bias-corrected
formula.
- covarianceToCorrelation(RealMatrix) - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Derives a correlation matrix from a covariance matrix.
- createAdaptor(RandomGenerator) - Static method in class org.apache.commons.math.random.RandomAdaptor
-
Factory method to create a Random
using the supplied
RandomGenerator
.
- createArithmeticException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createArithmeticException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new ArithmeticException
with specified formatted detail message.
- createArrayIndexOutOfBoundsException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createArrayIndexOutOfBoundsException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new ArrayIndexOutOfBoundsException
with specified formatted detail message.
- createBigIdentityMatrix(int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBigMatrix(double[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBigMatrix(BigDecimal[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBigMatrix(BigDecimal[][], boolean) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBigMatrix(String[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createBlocksLayout(Field<T>, int, int) - Static method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Create a data array in blocks layout.
- createBlocksLayout(int, int) - Static method in class org.apache.commons.math.linear.BlockRealMatrix
-
Create a data array in blocks layout.
- createChebyshevPolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Create a Chebyshev polynomial of the first kind.
- createColumnBigMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createColumnBigMatrix(BigDecimal[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createColumnBigMatrix(String[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createColumnFieldMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a column
FieldMatrix
using the data from the input
array.
- createColumnRealMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a column
RealMatrix
using the data from the input
array.
- createComplex(double, double) - Method in class org.apache.commons.math.complex.Complex
-
Create a complex number given the real and imaginary parts.
- createConcurrentModificationException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createConcurrentModificationException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new ConcurrentModificationException
with specified formatted detail message.
- createContributingStatistics() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Creates and returns a SummaryStatistics
whose data will be
aggregated with those of this AggregateSummaryStatistics
.
- createEOFException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createEOFException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new EOFException
with specified formatted detail message.
- createFieldDiagonalMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns a diagonal matrix with specified elements.
- createFieldIdentityMatrix(Field<T>, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns dimension x dimension
identity matrix.
- createFieldMatrix(Field<T>, int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createFieldMatrix(T[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns a
FieldMatrix
whose entries are the the values in the
the input array.
- createFieldVector(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a
FieldVector
using the data from the input array.
- createHermitePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Create a Hermite polynomial.
- createIllegalArgumentException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createIllegalArgumentException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new IllegalArgumentException
with specified formatted detail message.
- createIllegalArgumentException(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new IllegalArgumentException
with specified nested
Throwable
root cause.
- createIllegalStateException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createIllegalStateException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new IllegalStateException
with specified formatted detail message.
- createInternalError(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createIOException(Throwable) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new IOException
with specified nested
Throwable
root cause.
- createLaguerrePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Create a Laguerre polynomial.
- createLegendrePolynomial(int) - Static method in class org.apache.commons.math.analysis.polynomials.PolynomialsUtils
-
Create a Legendre polynomial.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Create a new RealMatrix of the same type as the instance with the supplied
row and column dimensions.
- createMatrix(int, int) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Create a new FieldMatrix of the same type as the instance with the supplied
row and column dimensions.
- createNoSuchElementException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createNoSuchElementException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new NoSuchElementException
with specified formatted detail message.
- createNullPointerException(String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createNullPointerException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Deprecated.
in 2.2. Checks for "null" must not be performed in Commons-Math.
- createParametersGuesser(WeightedObservedPoint[]) - Method in class org.apache.commons.math.optimization.fitting.GaussianFitter
-
Factory method to create a GaussianParametersGuesser
instance initialized with the specified observations.
- createParseException(int, String, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- createParseException(int, Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
Constructs a new ParseException
with specified
formatted detail message.
- createRealDiagonalMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns a diagonal matrix with specified elements.
- createRealIdentityMatrix(int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns dimension x dimension
identity matrix.
- createRealMatrix(int, int) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createRealMatrix(double[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Returns a
RealMatrix
whose entries are the the values in the
the input array.
- createRealVector(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a
RealVector
using the data from the input array.
- createRowBigMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createRowBigMatrix(BigDecimal[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createRowBigMatrix(String[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- createRowFieldMatrix(T[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a row
FieldMatrix
using the data from the input
array.
- createRowRealMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
Creates a row
RealMatrix
using the data from the input
array.
- createUnsupportedOperationException(Localizable, Object...) - Static method in exception org.apache.commons.math.MathRuntimeException
-
- crossover(Chromosome, Chromosome) - Method in interface org.apache.commons.math.genetics.CrossoverPolicy
-
Perform a crossover operation on the given chromosomes.
- crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math.genetics.OnePointCrossover
-
Performs one point crossover.
- CrossoverPolicy - Interface in org.apache.commons.math.genetics
-
Policy used to create a pair of new chromosomes by performing a crossover
operation on a source pair of chromosomes.
- crossProduct(Vector3D, Vector3D) - Static method in class org.apache.commons.math.geometry.Vector3D
-
Compute the cross-product of two vectors.
- cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.AbstractDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(int, int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
For this distribution, X, this method returns P(X ≤ x).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
For this distribution, X, this method returns P(X < x
).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.Distribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(double, double) - Method in interface org.apache.commons.math.distribution.Distribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
For this distribution, X, this method returns P(X < x).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
For this distribution, X, this method returns P(X ≤ x).
- cumulativeProbability(int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
-
For a random variable X whose values are distributed according
to this distribution, this method returns P(X ≤ x).
- cumulativeProbability(int, int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
-
For this distribution, X, this method returns P(x0 ≤ X ≤ x1).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
For this distribution, X, this method returns P(X < x
).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
For this distribution, X, this method returns P(X ≤ x).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
The probability distribution function P(X <= x) for a Poisson
distribution.
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
For this distribution, X, this method returns P(X < x
).
- cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
For this distribution, X, this method returns P(X < x
).
- cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
The probability distribution function P(X <= x) for a Zipf distribution.
- currentState - Variable in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
current state
- CurveFitter - Class in org.apache.commons.math.optimization.fitting
-
Fitter for parametric univariate real functions y = f(x).
- CurveFitter(DifferentiableMultivariateVectorialOptimizer) - Constructor for class org.apache.commons.math.optimization.fitting.CurveFitter
-
Simple constructor.
- g(double, double[]) - Method in interface org.apache.commons.math.ode.events.EventHandler
-
Compute the value of the switching function.
- g(double, double[], double[][], double[][]) - Method in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
-
Deprecated.
Compute the value of the switching function.
- Gamma - Class in org.apache.commons.math.special
-
This is a utility class that provides computation methods related to the
Gamma family of functions.
- GAMMA - Static variable in class org.apache.commons.math.special.Gamma
-
- GammaDistribution - Interface in org.apache.commons.math.distribution
-
The Gamma Distribution.
- GammaDistributionImpl - Class in org.apache.commons.math.distribution
-
- GammaDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.GammaDistributionImpl
-
Create a new gamma distribution with the given alpha and beta values.
- GammaDistributionImpl(double, double, double) - Constructor for class org.apache.commons.math.distribution.GammaDistributionImpl
-
Create a new gamma distribution with the given alpha and beta values.
- GAUSSIAN_MODE - Static variable in class org.apache.commons.math.random.ValueServer
-
Gaussian random deviates with mean = μ, std dev = σ.
- GaussianDerivativeFunction - Class in org.apache.commons.math.optimization.fitting
-
- GaussianDerivativeFunction(double, double, double) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianDerivativeFunction
-
Constructs an instance with the specified parameters.
- GaussianDerivativeFunction(double[]) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianDerivativeFunction
-
Constructs an instance with the specified parameters.
- GaussianFitter - Class in org.apache.commons.math.optimization.fitting
-
- GaussianFitter(DifferentiableMultivariateVectorialOptimizer) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianFitter
-
Constructs an instance using the specified optimizer.
- GaussianFunction - Class in org.apache.commons.math.optimization.fitting
-
A Gaussian function.
- GaussianFunction(double, double, double, double) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Constructs an instance with the specified parameters.
- GaussianFunction(double[]) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Constructs an instance with the specified parameters.
- GaussianParametersGuesser - Class in org.apache.commons.math.optimization.fitting
-
- GaussianParametersGuesser(WeightedObservedPoint[]) - Constructor for class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
-
Constructs instance with the specified observed points.
- GaussianRandomGenerator - Class in org.apache.commons.math.random
-
This class is a gaussian normalized random generator for scalars.
- GaussianRandomGenerator(RandomGenerator) - Constructor for class org.apache.commons.math.random.GaussianRandomGenerator
-
Create a new generator.
- GaussNewtonEstimator - Class in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- GaussNewtonEstimator() - Constructor for class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Simple constructor with default settings.
- GaussNewtonEstimator(int, double, double) - Constructor for class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Simple constructor.
- GaussNewtonOptimizer - Class in org.apache.commons.math.optimization.general
-
Gauss-Newton least-squares solver.
- GaussNewtonOptimizer(boolean) - Constructor for class org.apache.commons.math.optimization.general.GaussNewtonOptimizer
-
Simple constructor with default settings.
- gcd(int, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Gets the greatest common divisor of the absolute value of two numbers,
using the "binary gcd" method which avoids division and modulo
operations.
- gcd(long, long) - Static method in class org.apache.commons.math.util.MathUtils
-
Gets the greatest common divisor of the absolute value of two numbers,
using the "binary gcd" method which avoids division and modulo
operations.
- GeneticAlgorithm - Class in org.apache.commons.math.genetics
-
Implementation of a genetic algorithm.
- GeneticAlgorithm(CrossoverPolicy, double, MutationPolicy, double, SelectionPolicy) - Constructor for class org.apache.commons.math.genetics.GeneticAlgorithm
-
- geoMean - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
geoMean of values that have been added
- GeometricMean - Class in org.apache.commons.math.stat.descriptive.moment
-
- GeometricMean() - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Create a GeometricMean instance
- GeometricMean(GeometricMean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Copy constructor, creates a new GeometricMean
identical
to the original
- GeometricMean(SumOfLogs) - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Create a GeometricMean instance using the given SumOfLogs instance
- geometricMean(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the geometric mean of the entries in the input array, or
Double.NaN
if the array is empty.
- geometricMean(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the geometric mean of the entries in the specified portion of
the input array, or Double.NaN
if the designated subarray
is empty.
- get(int) - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Get the stored value associated with the given key
- get(int) - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Get the stored value associated with the given key
- getA() - Method in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Gets a parameter value.
- getA(int, double) - Method in class org.apache.commons.math.util.ContinuedFraction
-
Access the n-th a coefficient of the continued fraction.
- getA1() - Method in class org.apache.commons.math.geometry.RotationOrder
-
Get the axis of the first rotation.
- getA2() - Method in class org.apache.commons.math.geometry.RotationOrder
-
Get the axis of the second rotation.
- getA3() - Method in class org.apache.commons.math.geometry.RotationOrder
-
Get the axis of the second rotation.
- getAbsoluteAccuracy() - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Get the actual absolute accuracy.
- getAbsoluteAccuracy() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Get the actual absolute accuracy.
- getAbsoluteAccuracy() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the actual absolute accuracy.
- getAllParameters() - Method in interface org.apache.commons.math.estimation.EstimationProblem
-
Deprecated.
Get all the parameters of the problem.
- getAllParameters() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Get all the parameters of the problem.
- getAlpha() - Method in interface org.apache.commons.math.distribution.BetaDistribution
-
Access the shape parameter, alpha
- getAlpha() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the shape parameter, alpha
- getAlpha() - Method in interface org.apache.commons.math.distribution.GammaDistribution
-
Access the shape parameter, alpha
- getAlpha() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the shape parameter, alpha
- getAlpha() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the azimuth of the vector.
- getAmplitude() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
-
Get the amplitude a.
- getAngle() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the angle of the rotation.
- getAngles(RotationOrder) - Method in class org.apache.commons.math.geometry.Rotation
-
Get the Cardan or Euler angles corresponding to the instance.
- getArgument() - Method in class org.apache.commons.math.complex.Complex
-
Compute the argument of this complex number.
- getArgument() - Method in exception org.apache.commons.math.exception.MathIllegalNumberException
-
- getArgument() - Method in exception org.apache.commons.math.FunctionEvaluationException
-
Returns the function argument that caused this exception.
- getArguments() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in exception org.apache.commons.math.MathException
-
Gets the arguments used to build the message of this throwable.
- getArguments() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the arguments used to build the message of this throwable.
- getArity() - Method in class org.apache.commons.math.genetics.TournamentSelection
-
Gets the arity (number of chromosomes drawn to the tournament).
- getAvailableLocales() - Static method in class org.apache.commons.math.complex.ComplexFormat
-
Get the set of locales for which complex formats are available.
- getAvailableLocales() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Get the set of locales for which complex formats are available.
- getAvailableLocales() - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Get the set of locales for which complex formats are available.
- getAvailableLocales() - Static method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the set of locales for which 3D vectors formats are available.
- getAvailableLocales() - Static method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the set of locales for which real vectors formats are available.
- getAxis() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the normalized axis of the rotation.
- getB() - Method in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Gets b parameter value.
- getB(int, double) - Method in class org.apache.commons.math.util.ContinuedFraction
-
Access the n-th b coefficient of the continued fraction.
- getBeta() - Method in interface org.apache.commons.math.distribution.BetaDistribution
-
Access the shape parameter, beta
- getBeta() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the shape parameter, beta
- getBeta() - Method in interface org.apache.commons.math.distribution.GammaDistribution
-
Access the scale parameter, beta
- getBeta() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the scale parameter, beta
- getBinCount() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Returns the number of bins.
- getBinCount() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Returns the number of bins.
- getBinStats() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Returns a list of
SummaryStatistics
containing statistics describing the values in each of the bins.
- getBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Returns a List of
SummaryStatistics
instances containing
statistics describing the values in each of the bins.
- getBoundIsAllowed() - Method in exception org.apache.commons.math.exception.NumberIsTooLargeException
-
- getBoundIsAllowed() - Method in exception org.apache.commons.math.exception.NumberIsTooSmallException
-
- getC() - Method in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Gets c parameter value.
- getCenter() - Method in class org.apache.commons.math.stat.clustering.Cluster
-
Get the point chosen to be the center of this cluster.
- getCenters() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Returns a copy of the centers array.
- getChiSquare(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the Chi-Square value.
- getChiSquare() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get a Chi-Square-like value assuming the N residuals follow N
distinct normal distributions centered on 0 and whose variances are
the reciprocal of the weights.
- getChiSquareTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0
- getChromosomes() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Access the list of chromosomes.
- getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Returns a copy of the coefficients array.
- getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Returns a copy of the coefficients array.
- getCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Returns a copy of the coefficients array.
- getCoefficients() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
-
Get the coefficients of the constraint (left hand side).
- getCoefficients() - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Get the coefficients of the linear equation being optimized.
- getColumn(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in column number col
as an array.
- getColumn(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in column number col
as an array.
- getColumn(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in column number col
as an array.
- getColumn(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in column number col
as an array.
- getColumn(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in column number col
as an array.
- getColumn(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in column number col
as an array.
- getColumn(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in column number col
as an array.
- getColumn(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in column number col
as an array.
- getColumnAsDoubleArray(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in column number col
as an array
of double values.
- getColumnAsDoubleArray(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in column number col
as an array
of double values.
- getColumnDimension() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in interface org.apache.commons.math.linear.AnyMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns the number of columns in the matrix.
- getColumnDimension() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Returns the number of columns in the matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in column number column
as a column matrix.
- getColumnVector(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in column number column
as a vector.
- getColumnVector(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in column number column
as a vector.
- getConditionNumber() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Return the condition number of the matrix.
- getConditionNumber() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Return the condition number of the matrix.
- getConstantTerm() - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Get the constant of the linear equation being optimized.
- getContractionCriteria() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
The contraction criteria defines when the internal array will contract
to store only the number of elements in the element array.
- getConvergence() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the convergence threshold for event localization.
- getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the convergence checker.
- getConvergenceChecker() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the convergence checker.
- getCorrelationMatrix() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Returns the correlation matrix
- getCorrelationMatrix() - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Calculate the Spearman Rank Correlation Matrix.
- getCorrelationPValues() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Returns a matrix of p-values associated with the (two-sided) null
hypothesis that the corresponding correlation coefficient is zero.
- getCorrelationStandardErrors() - Method in class org.apache.commons.math.stat.correlation.PearsonsCorrelation
-
Returns a matrix of standard errors associated with the estimates
in the correlation matrix.
getCorrelationStandardErrors().getEntry(i,j)
is the standard
error associated with getCorrelationMatrix.getEntry(i,j)
- getCostEvaluations() - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the number of cost evaluations.
- getCount(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- getCount(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values = v.
- getCount(int) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values = v.
- getCount(long) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values = v.
- getCount(char) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values = v.
- getCount(int...) - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Convert to unidimensional counter.
- getCount() - Method in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Get the current unidimensional counter slot.
- getCount(int) - Method in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Get the current count in the selected dimension.
- getCounts(int) - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Convert to multidimensional counter.
- getCounts() - Method in class org.apache.commons.math.util.MultidimensionalCounter.Iterator
-
Get the current multidimensional counter slots.
- getCovariance(double) - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the n × n covariance matrix.
- getCovariance(double) - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the n × n covariance matrix.
- getCovariance() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the covariance matrix of the values that have been added.
- getCovariance() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns the covariance of the available values.
- getCovariance() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the covariance matrix of the values that have been added.
- getCovarianceMatrix() - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Returns the covariance matrix
- getCovariances(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the covariance matrix of unbound estimated parameters.
- getCovariances(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
-
Deprecated.
Get the covariance matrix of estimated parameters.
- getCovariances() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the covariance matrix of optimized parameters.
- getCrossoverPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the crossover policy.
- getCrossoverRate() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the crossover rate.
- getCumFreq(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- getCumFreq(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative frequency of values less than or equal to v.
- getCumFreq(int) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative frequency of values less than or equal to v.
- getCumFreq(long) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative frequency of values less than or equal to v.
- getCumFreq(char) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative frequency of values less than or equal to v.
- getCumPct(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- getCumPct(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative percentage of values less than or equal to v
(as a proportion between 0 and 1).
- getCumPct(int) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative percentage of values less than or equal to v
(as a proportion between 0 and 1).
- getCumPct(long) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative percentage of values less than or equal to v
(as a proportion between 0 and 1).
- getCumPct(char) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the cumulative percentage of values less than or equal to v
(as a proportion between 0 and 1).
- getCurrentSignedStepsize() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the current signed value of the integration stepsize.
- getCurrentSignedStepsize() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get the current signed value of the integration stepsize.
- getCurrentSignedStepsize() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the current signed value of the integration stepsize.
- getCurrentStepStart() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the current value of the step start time ti.
- getCurrentStepStart() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get the current value of the step start time ti.
- getCurrentStepStart() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Get the current value of the step start time ti.
- getCurrentStepStart() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the current value of the step start time ti.
- getCurrentTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the current grid point time.
- getCurrentTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the current soft grid point time.
- getCurrentTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the current grid point time.
- getD() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the block diagonal matrix D of the decomposition.
- getD() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the block diagonal matrix D of the decomposition.
- getD() - Method in class org.apache.commons.math.optimization.fitting.GaussianFunction
-
Gets d parameter value.
- getData() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns vector entries as a double array.
- getData() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns vector entries as a T array.
- getData() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns vector entries as a double array.
- getData() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in interface org.apache.commons.math.linear.FieldVector
-
Returns vector entries as a T array.
- getData() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Returns vector entries as a double array.
- getData() - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns matrix entries as a two-dimensional array.
- getData() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getData() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns vector entries as a double array.
- getData() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Returns vector entries as a T array.
- getData() - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Get a copy of the stored data array.
- getDataAsDoubleArray() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getDataAsDoubleArray() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns matrix entries as a two-dimensional array.
- getDataRef() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns a reference to the underlying data array.
- getDataRef() - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Get a reference to the stored data array.
- getDecimalDigits() - Method in class org.apache.commons.math.dfp.DfpDec
-
Get the number of decimal digits this class is going to represent.
- getDefaultNumberFormat() - Static method in class org.apache.commons.math.fraction.AbstractFormat
-
Create a default number format.
- getDefaultNumberFormat(Locale) - Static method in class org.apache.commons.math.fraction.AbstractFormat
-
Create a default number format.
- getDefaultNumberFormat() - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Create a default number format.
- getDefaultNumberFormat() - Static method in class org.apache.commons.math.util.CompositeFormat
-
Create a default number format.
- getDefaultNumberFormat(Locale) - Static method in class org.apache.commons.math.util.CompositeFormat
-
Create a default number format.
- getDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
-
Access the degrees of freedom.
- getDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Access the degrees of freedom.
- getDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.TDistribution
-
Access the degrees of freedom.
- getDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Access the degrees of freedom.
- getDelta() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the elevation of the vector.
- getDenominator() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the denominator as a BigInteger
.
- getDenominator() - Method in class org.apache.commons.math.fraction.Fraction
-
Access the denominator.
- getDenominatorAsInt() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the denominator as a int.
- getDenominatorAsLong() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the denominator as a long.
- getDenominatorDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.FDistribution
-
Access the denominator degrees of freedom.
- getDenominatorDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the denominator degrees of freedom.
- getDenominatorFormat() - Method in class org.apache.commons.math.fraction.AbstractFormat
-
Access the denominator format.
- getDeterminant() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Deprecated.
- getDeterminant() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the determinant of this matrix.
- getDeterminant() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the determinant of this matrix.
- getDeterminant() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
-
Return the determinant of the matrix
- getDeterminant() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Return the determinant of the matrix
- getDeterminant() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Return the determinant of the matrix
- getDeterminant() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Return the determinant of the matrix
- getDeterminant() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Return the determinant of the matrix
- getDeterminant() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Return the determinant of the matrix
- getDeterminant() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Return the determinant of the matrix
- getDeterminant() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Return the determinant of the matrix
- getDeterminant() - Method in interface org.apache.commons.math.linear.RealMatrix
-
- getDimension() - Method in exception org.apache.commons.math.exception.DimensionMismatchException
-
- getDimension() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns the size of the vector.
- getDimension() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the size of the vector.
- getDimension() - Method in interface org.apache.commons.math.linear.FieldVector
-
Returns the size of the vector.
- getDimension() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Returns the size of the vector.
- getDimension() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the size of the vector.
- getDimension() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Returns the size of the vector.
- getDimension() - Method in class org.apache.commons.math.ode.FirstOrderConverter
-
Get the dimension of the problem.
- getDimension() - Method in interface org.apache.commons.math.ode.FirstOrderDifferentialEquations
-
Get the dimension of the problem.
- getDimension() - Method in interface org.apache.commons.math.ode.SecondOrderDifferentialEquations
-
Get the dimension of the problem.
- getDimension() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the dimension of the data
- getDimension() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns the dimension of the data
- getDimension() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the dimension of the data
- getDimension() - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Get the number of dimensions of the multidimensional counter.
- getDimension1() - Method in exception org.apache.commons.math.DimensionMismatchException
-
Deprecated.
Get the first dimension
- getDimension2() - Method in exception org.apache.commons.math.DimensionMismatchException
-
Deprecated.
Get the second dimension
- getDirection() - Method in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
- getDistance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getDistance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getDistance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getDistance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getDistance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getDistance(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to compute distance.
- getDistance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getDistance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getDistance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getDistance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Access the domain value lower bound, based on p
, used to
bracket a PDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a PDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a PDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a PDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a CDF root.
- getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Access the domain value lower bound, based on p
, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Access the domain value upper bound, based on p
, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a PDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a CDF root.
- getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Access the domain value upper bound, based on p
, used to
bracket a PDF root.
- getDuplicateAbscissa() - Method in exception org.apache.commons.math.DuplicateSampleAbscissaException
-
Get the duplicate abscissa.
- getE() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant e.
- getEigenvector(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns a copy of the ith eigenvector of the original matrix.
- getEigenvector(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns a copy of the ith eigenvector of the original matrix.
- getElement(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the element at the specified index
- getElement(int) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the element at the specified index
- getElement(int) - Method in interface org.apache.commons.math.util.DoubleArray
-
Returns the element at the specified index.
- getElement(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns the element at the specified index
- getElements() - Method in interface org.apache.commons.math.util.DoubleArray
-
Returns a double[] array containing the elements of this
DoubleArray
.
- getElements() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns a double array containing the elements of this
ResizableArray
.
- getElitismRate() - Method in class org.apache.commons.math.genetics.ElitisticListPopulation
-
Access the elitism rate.
- getEmpiricalDistribution() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for property empiricalDistribution.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Returns the entry in the specified index.
- getEntry(int) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int) - Method in interface org.apache.commons.math.linear.FieldVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entry in the specified row and column.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns the entry in the specified row and column.
- getEntry(int) - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the entry in the specified index.
- getEntry(int, int) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Returns the entry in the specified row and column.
- getEntry(int) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Returns the entry in the specified index.
- getEntryAsDouble(int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entry in the specified row and column as a double.
- getEntryAsDouble(int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entry in the specified row and column as a double.
- getESplit() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant e split in two pieces.
- getEstimate() - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Get the current estimate of the parameter
- getEvaluations() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the number of evaluations of the differential equations function.
- getEvaluations() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get the number of evaluations of the differential equations function.
- getEvaluations() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the number of evaluations of the differential equations function.
- getEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEvaluations() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getEvaluations() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Get the number of evaluations of the objective function.
- getEventHandler() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the underlying event handler.
- getEventHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get all the event handlers that have been added to the integrator.
- getEventHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get all the event handlers that have been added to the integrator.
- getEventHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get all the event handlers that have been added to the integrator.
- getEventsHandlers() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Get all the events handlers that have been added to the manager.
- getEventsStates() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Get all the events state wrapping the handlers that have been added to the manager.
- getEventTime() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Get the occurrence time of the first event triggered in the
last evaluated step.
- getEventTime() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the occurrence time of the event triggered in the current step.
- getExpansionFactor() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
The expansion factor controls the size of a new array when an array
needs to be expanded.
- getExpansionMode() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
The expansionMode
determines whether the internal storage
array grows additively (ADDITIVE_MODE) or multiplicatively
(MULTIPLICATIVE_MODE) when it is expanded.
- getExponent() - Method in interface org.apache.commons.math.distribution.ZipfDistribution
-
Get the exponent characterising the distribution.
- getExponent() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Get the exponent characterising the distribution.
- getExponent(double) - Static method in class org.apache.commons.math.util.FastMath
-
Return the exponent of a double number, removing the bias.
- getExponent(float) - Static method in class org.apache.commons.math.util.FastMath
-
Return the exponent of a float number, removing the bias.
- getFHi() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getField() - Method in class org.apache.commons.math.complex.Complex
-
Get the
Field
to which the instance belongs.
- getField() - Method in class org.apache.commons.math.dfp.Dfp
-
- getField() - Method in interface org.apache.commons.math.FieldElement
-
Get the
Field
to which the instance belongs.
- getField() - Method in class org.apache.commons.math.fraction.BigFraction
-
Get the
Field
to which the instance belongs.
- getField() - Method in class org.apache.commons.math.fraction.Fraction
-
Get the
Field
to which the instance belongs.
- getField() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Get the type of field elements of the matrix.
- getField() - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Get the type of field elements of the vector.
- getField() - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Get the type of field elements of the matrix.
- getField() - Method in interface org.apache.commons.math.linear.FieldVector
-
Get the type of field elements of the vector.
- getField() - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Get the type of field elements of the vector.
- getField() - Method in class org.apache.commons.math.util.BigReal
-
Get the
Field
to which the instance belongs.
- getFinalTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Get the final integration time.
- getFirst() - Method in class org.apache.commons.math.genetics.ChromosomePair
-
Access the first chromosome.
- getFitness() - Method in class org.apache.commons.math.genetics.Chromosome
-
Access the fitness of this chromosome.
- getFittestChromosome() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Access the fittest chromosome in this population.
- getFittestChromosome() - Method in interface org.apache.commons.math.genetics.Population
-
Access the fittest chromosome in this population.
- getFLow() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getFMid() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getFormat() - Method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the components format.
- getFormat() - Method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the components format.
- getFrobeniusNorm() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
- getFrobeniusNorm() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
- getFrobeniusNorm() - Method in interface org.apache.commons.math.linear.RealMatrix
-
- getFunctionValue() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Get the result of the last run of the solver.
- getFunctionValue() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Get the result of the last run of the solver.
- getFunctionValue() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getFunctionValue() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getFunctionValue() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getFunctionValueAccuracy() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Get the actual function value accuracy.
- getFunctionValueAccuracy() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Get the actual function value accuracy.
- getGeneralPattern() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in exception org.apache.commons.math.MathException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGeneralPattern() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the localizable pattern used to build the general part of the message of this throwable.
- getGenerationsEvolved() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the number of generations evolved to
reach
StoppingCondition
in the last run.
- getGenerator() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Get the underlying normalized components generator.
- getGeneratorUpperBounds() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Returns a fresh copy of the array of upper bounds of the subintervals
of [0,1] used in generating data from the empirical distribution.
- getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured geometric mean implementation
- getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured geometric mean implementation
- getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured geometric mean implementation
- getGeoMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured geometric mean implementation
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the geometric mean of all the aggregated data.
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getGeometricMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
geometric mean of the ith entries of the arrays
that correspond to each multivariate sample
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the geometric mean of the values that have been added.
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the geometric mean of the values that have been added.
- getGeometricMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured geometric mean implementation.
- getGlobalCurrentTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the current global grid point time.
- getGlobalPreviousTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the previous global grid point time.
- getGoalType() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- getGradientEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the number of evaluations of the objective function gradient.
- getGradientEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the number of evaluations of the objective function gradient.
- getGradientEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the number of evaluations of the objective function gradient.
- getGuessedAmplitude() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Get the guessed amplitude a.
- getGuessedPhase() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Get the guessed phase φ.
- getGuessedPulsation() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Get the guessed pulsation ω.
- getH() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Returns the Householder reflector vectors.
- getH() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Returns the Householder reflector vectors.
- getHi() - Method in exception org.apache.commons.math.exception.OutOfRangeException
-
- getHi() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getIEEEFlags() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the IEEE 854 status flags.
- getImagEigenvalue(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the imaginary part of the ith eigenvalue of the original matrix.
- getImagEigenvalue(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the imaginary part of the ith eigenvalue of the original matrix.
- getImagEigenvalues() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns a copy of the imaginary parts of the eigenvalues of the original matrix.
- getImagEigenvalues() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns a copy of the imaginary parts of the eigenvalues of the original matrix.
- getImaginary() - Method in class org.apache.commons.math.complex.Complex
-
Access the imaginary part.
- getImaginaryCharacter() - Method in class org.apache.commons.math.complex.ComplexFormat
-
Access the imaginaryCharacter.
- getImaginaryFormat() - Method in class org.apache.commons.math.complex.ComplexFormat
-
Access the imaginaryFormat.
- getImproperInstance() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Returns the default complex format for the current locale.
- getImproperInstance(Locale) - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Returns the default complex format for the given locale.
- getImproperInstance() - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Returns the default complex format for the current locale.
- getImproperInstance(Locale) - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Returns the default complex format for the given locale.
- getIndex() - Method in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
Get the index of the wrong value.
- getIndex() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
-
Get the index of the entry.
- getIndex() - Method in class org.apache.commons.math.linear.RealVector.Entry
-
Get the index of the entry.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialDomain(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the initial domain value, based on p
, used to
bracket a CDF root.
- getInitialTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Get the initial integration time.
- getInstance() - Static method in class org.apache.commons.math.complex.ComplexField
-
Get the unique instance.
- getInstance() - Static method in class org.apache.commons.math.complex.ComplexFormat
-
Returns the default complex format for the current locale.
- getInstance(Locale) - Static method in class org.apache.commons.math.complex.ComplexFormat
-
Returns the default complex format for the given locale.
- getInstance() - Static method in class org.apache.commons.math.fraction.BigFractionField
-
Get the unique instance.
- getInstance() - Static method in class org.apache.commons.math.fraction.FractionField
-
Get the unique instance.
- getInstance() - Static method in class org.apache.commons.math.geometry.Vector3DFormat
-
Returns the default 3D vector format for the current locale.
- getInstance(Locale) - Static method in class org.apache.commons.math.geometry.Vector3DFormat
-
Returns the default 3D vector format for the given locale.
- getInstance() - Static method in class org.apache.commons.math.linear.RealVectorFormat
-
Returns the default real vector format for the current locale.
- getInstance(Locale) - Static method in class org.apache.commons.math.linear.RealVectorFormat
-
Returns the default real vector format for the given locale.
- getInstance(int) - Static method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Get the Nordsieck transformer for a given number of steps.
- getInstance() - Static method in class org.apache.commons.math.ode.sampling.DummyStepHandler
-
Get the only instance.
- getInstance() - Static method in class org.apache.commons.math.util.BigRealField
-
Get the unique instance.
- getIntercept() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the intercept of the estimated regression line.
- getInterceptStdErr() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getInternalValues() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns the internal storage array.
- getInterpolatedDerivatives() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the derivatives of the state vector of the interpolated point.
- getInterpolatedDerivatives() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the derivatives of the state vector of the interpolated point.
- getInterpolatedDyDp() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the partial derivatives of the state vector with respect to
the ODE parameters of the interpolated point.
- getInterpolatedDyDpDot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the time derivatives of the jacobian of the state vector
with respect to the ODE parameters of the interpolated point.
- getInterpolatedDyDy0() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the partial derivatives of the state vector with respect to
the initial state of the interpolated point.
- getInterpolatedDyDy0Dot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the time derivatives of the jacobian of the state vector
with respect to the initial state of the interpolated point.
- getInterpolatedState() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Get the state vector of the interpolated point.
- getInterpolatedState() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the state vector of the interpolated point.
- getInterpolatedState() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the state vector of the interpolated point.
- getInterpolatedStateVariation() - Method in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
Get the state vector variation from current to interpolated state.
- getInterpolatedTime() - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Get the time of the interpolated point.
- getInterpolatedTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the time of the interpolated point.
- getInterpolatedTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the time of the interpolated point.
- getInterpolatedTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the time of the interpolated point.
- getInterpolatedY() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the state vector of the interpolated point.
- getInterpolatedYDot() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the time derivatives of the state vector of the interpolated point.
- getInterpolatingPoints() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Returns a copy of the interpolating points array.
- getInterpolatingValues() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionLagrangeForm
-
Returns a copy of the interpolating values array.
- getInverse() - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Get the inverse (or pseudo-inverse) of the decomposed matrix.
- getInverse() - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Get the inverse (or pseudo-inverse) of the decomposed matrix.
- getIterationCount() - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Get the number of iterations in the last run of the algorithm.
- getIterationCount() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Get the number of iterations in the last run of the algorithm.
- getIterationCount() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the number of iterations in the last run of the algorithm.
- getIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the number of iterations realized by the algorithm.
- getIterations() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getJacobianEvaluations() - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the number of jacobian evaluations.
- getJacobianEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the number of evaluations of the objective function jacobian .
- getJacobianEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the number of evaluations of the objective function jacobian .
- getJacobianEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the number of evaluations of the objective function jacobian .
- getKnots() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
-
Returns an array copy of the knot points.
- getKurtosis() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the Kurtosis of the available values.
- getKurtosisImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured kurtosis implementation.
- getL() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
-
Returns the matrix L of the decomposition.
- getL() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Returns the matrix L of the decomposition.
- getL() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Returns the matrix L of the decomposition.
- getL() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Returns the matrix L of the decomposition.
- getL() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Returns the matrix L of the decomposition.
- getL() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Returns the matrix L of the decomposition.
- getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getL1Distance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getL1Distance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getL1Distance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getL1Distance(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getL1Distance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getL1Distance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getL1Distance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getL1Distance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getL1Norm() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns the L1 norm of the vector.
- getL1Norm() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the L1 norm of the vector.
- getL1Norm() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the L1 norm of the vector.
- getLength() - Method in class org.apache.commons.math.genetics.AbstractListChromosome
-
Returns the length of the chromosome.
- getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Distance between two vectors.
- getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getLInfDistance(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Distance between two vectors.
- getLInfDistance(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getLInfDistance(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Distance between two vectors.
- getLInfDistance(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getLInfDistance(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Distance between two vectors.
- getLInfNorm() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns the L∞ norm of the vector.
- getLInfNorm() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the L∞ norm of the vector.
- getLInfNorm() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the L∞ norm of the vector.
- getLn10() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(10).
- getLn2() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(2).
- getLn2Split() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(2) split in two pieces.
- getLn5() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(5).
- getLn5Split() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant ln(5) split in two pieces.
- getLo() - Method in exception org.apache.commons.math.exception.OutOfRangeException
-
- getLo() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getLocalizedMessage() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in exception org.apache.commons.math.MathException
-
Gets the message in the system default locale.
- getLocalizedMessage() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the message in the system default locale.
- getLocalizedString(Locale) - Method in class org.apache.commons.math.exception.util.DummyLocalizable
-
Get the localized string.
- getLocalizedString(Locale) - Method in interface org.apache.commons.math.exception.util.Localizable
-
Get the localized string.
- getLocalizedString(Locale) - Method in enum org.apache.commons.math.exception.util.LocalizedFormats
-
Get the localized string.
- getLT() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
-
Returns the transpose of the matrix L of the decomposition.
- getLT() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Returns the transpose of the matrix L of the decomposition.
- getLUMatrix() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the LU decomposition as a BigMatrix.
- getMainSetDimension() - Method in interface org.apache.commons.math.ode.ExtendedFirstOrderDifferentialEquations
-
Return the dimension of the main set of equations.
- getMatrix() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the 3X3 matrix corresponding to the instance
- getMax() - Method in exception org.apache.commons.math.exception.NumberIsTooLargeException
-
- getMax() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- getMax() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the maximum of the available values
- getMax() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the maximum of the available values
- getMax() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getMax() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
maximum of the ith entries of the arrays
that correspond to each multivariate sample
- getMax() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the maximum of the available values
- getMax() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getMax() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the maximum of the values that have been added.
- getMax() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getMax() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the maximum of the values that have been added.
- getMaxCheckInterval() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the maximal time interval between events handler checks.
- getMaxEvaluations() - Method in exception org.apache.commons.math.MaxEvaluationsExceededException
-
Get the maximal number of evaluations allowed.
- getMaxEvaluations() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxEvaluations() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Get the maximal number of functions evaluations.
- getMaxGrowth() - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Get the maximal growth factor for stepsize control.
- getMaxGrowth() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Get the maximal growth factor for stepsize control.
- getMaximalIterationCount() - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Get the upper limit for the number of iterations.
- getMaximalIterationCount() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Get the upper limit for the number of iterations.
- getMaximalIterationCount() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the upper limit for the number of iterations.
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured maximum implementation.
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured maximum implementation
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured maximum implementation
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured maximum implementation
- getMaxImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured maximum implementation
- getMaxIndex() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Get the index of the maximum entry.
- getMaxIterationCount() - Method in class org.apache.commons.math.ode.events.EventState
-
Get the upper limit in the iteration count for event localization.
- getMaxIterations() - Method in exception org.apache.commons.math.MaxIterationsExceededException
-
Get the maximal number of iterations allowed.
- getMaxIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxIterations() - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Get the maximal number of iterations of the algorithm.
- getMaxStep() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Get the maximal step.
- getMaxValue() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Get the value of the maximum entry.
- getMean() - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
-
Access the mean.
- getMean() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Access the mean.
- getMean() - Method in interface org.apache.commons.math.distribution.NormalDistribution
-
Access the mean.
- getMean() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the mean.
- getMean() - Method in interface org.apache.commons.math.distribution.PoissonDistribution
-
Get the mean for the distribution.
- getMean() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Get the Poisson mean for the distribution.
- getMean() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
mean of the ith entries of the arrays
that correspond to each multivariate sample
- getMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the mean of the values that have been added.
- getMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getMean() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the mean of the values that have been added.
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured mean implementation.
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured mean implementation
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured mean implementation
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured mean implementation
- getMeanImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured mean implementation
- getMeanSquareError() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of squared errors divided by the degrees of freedom,
usually abbreviated MSE.
- getMeasuredValue() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Get the measured value
- getMeasurements() - Method in interface org.apache.commons.math.estimation.EstimationProblem
-
Deprecated.
Get the measurements of an estimation problem.
- getMeasurements() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Get the measurements of an estimation problem.
- getMedian() - Method in interface org.apache.commons.math.distribution.CauchyDistribution
-
Access the median.
- getMedian() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the median.
- getMessage(Locale) - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Get the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Get the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the message in a specified locale.
- getMessage() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Get the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in exception org.apache.commons.math.MathException
-
Gets the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.MathException
-
Gets the message in a conventional US locale.
- getMessage(Locale) - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the message in a specified locale.
- getMessage() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the message in a conventional US locale.
- getMid() - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
- getMin() - Method in exception org.apache.commons.math.exception.NumberIsTooSmallException
-
- getMin() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- getMin() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the minimum of the available values
- getMin() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the minimum of the available values
- getMin() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getMin() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
minimum of the ith entries of the arrays
that correspond to each multivariate sample
- getMin() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the minimum of the available values
- getMin() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getMin() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the minimum of the values that have been added.
- getMin() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getMin() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the minimum of the values that have been added.
- getMinimalIterationCount() - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
-
Get the lower limit for the number of iterations.
- getMinimalIterationCount() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Get the lower limit for the number of iterations.
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured minimum implementation.
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured minimum implementation
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured minimum implementation
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured minimum implementation
- getMinImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured minimum implementation
- getMinIndex() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Get the index of the minimum entry.
- getMinReduction() - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Get the minimal reduction factor for stepsize control.
- getMinReduction() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Get the minimal reduction factor for stepsize control.
- getMinStep() - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Get the minimal step.
- getMinValue() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Get the value of the minimum entry.
- getMode() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for property mode.
- getMu() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for property mu.
- getMutationPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the mutation policy.
- getMutationRate() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the mutation rate.
- getN() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
-
Returns the number of spline segments = the number of polynomials
= the number of knot points - 1.
- getN() - Method in class org.apache.commons.math.stat.correlation.Covariance
-
Returns the number of observations (length of covariate vectors)
- getN() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Get the number of vectors in the sample.
- getN() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
-
Get the number of vectors in the sample.
- getN() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Returns the number of values that have been added.
- getN() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns the number of available values
- getN() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getN() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Returns the number of values that have been added.
- getN() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the number of available values
- getN() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the number of observations that have been added to the model.
- getName() - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
get the name of the parameter
- getName() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get the name of the method.
- getName() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get the name of the method.
- getNanStrategy() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
-
Return the NaNStrategy
- getNewtonCoefficients() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunctionNewtonForm
-
Returns a copy of coefficients in Newton form formula.
- getNext() - Method in class org.apache.commons.math.random.ValueServer
-
Returns the next generated value, generated according
to the mode value (see MODE constants).
- getNextValue() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Generates a random value from this distribution.
- getNextValue() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Generates a random value from this distribution.
- getNorm() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the L2 norm for the vector.
- getNorm() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
- getNorm() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Returns the L2 norm of the vector.
- getNorm() - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Returns the L2 norm of the vector.
- getNorm() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
- getNorm() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
- getNorm() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
- getNorm() - Method in interface org.apache.commons.math.linear.RealMatrix
-
- getNorm() - Method in interface org.apache.commons.math.linear.RealVector
-
Returns the L2 norm of the vector.
- getNorm() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the L2 norm of the matrix.
- getNorm() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the L2 norm of the matrix.
- getNorm1() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the L1 norm for the vector.
- getNormInf() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the L∞ norm for the vector.
- getNormSq() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the square of the norm for the vector.
- getNSteps() - Method in class org.apache.commons.math.ode.nonstiff.AdamsNordsieckTransformer
-
Get the number of steps of the method
(excluding the one being computed).
- getNumberOfElements() - Method in interface org.apache.commons.math.distribution.ZipfDistribution
-
Get the number of elements (e.g.
- getNumberOfElements() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Get the number of elements (e.g.
- getNumberOfSuccesses() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
Access the number of successes.
- getNumberOfSuccesses() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the number of successes.
- getNumberOfSuccesses() - Method in interface org.apache.commons.math.distribution.PascalDistribution
-
Access the number of successes for this distribution.
- getNumberOfSuccesses() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Access the number of successes for this distribution.
- getNumberOfTrials() - Method in interface org.apache.commons.math.distribution.BinomialDistribution
-
Access the number of trials for this distribution.
- getNumberOfTrials() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Access the number of trials for this distribution.
- getNumElements() - Method in interface org.apache.commons.math.util.DoubleArray
-
Returns the number of elements currently in the array.
- getNumElements() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns the number of elements currently in the array.
- getNumerator() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the numerator as a BigInteger
.
- getNumerator() - Method in class org.apache.commons.math.fraction.Fraction
-
Access the numerator.
- getNumeratorAsInt() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the numerator as a int.
- getNumeratorAsLong() - Method in class org.apache.commons.math.fraction.BigFraction
-
Access the numerator as a long.
- getNumeratorDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.FDistribution
-
Access the numerator degrees of freedom.
- getNumeratorDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Access the numerator degrees of freedom.
- getNumeratorFormat() - Method in class org.apache.commons.math.fraction.AbstractFormat
-
Access the numerator format.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Returns the mean of the distribution.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Returns the mean of the distribution.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Returns the mean of the distribution.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Returns the mean.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Returns the mean of the distribution.
- getNumericalMean() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Returns the mean.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Returns the variance.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Returns the variance of the distribution.
- getNumericalVariance() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Returns the variance.
- getNumGenerations() - Method in class org.apache.commons.math.genetics.FixedGenerationCount
-
- getObservations() - Method in class org.apache.commons.math.optimization.fitting.CurveFitter
-
Get the observed points.
- getOmegaInverse() - Method in class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
Get the inverse of the covariance.
- getOne() - Method in class org.apache.commons.math.complex.ComplexField
-
Get the multiplicative identity of the field.
- getOne() - Method in class org.apache.commons.math.dfp.Dfp
-
Get the constant 1.
- getOne() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant 1.
- getOne() - Method in interface org.apache.commons.math.Field
-
Get the multiplicative identity of the field.
- getOne() - Method in class org.apache.commons.math.fraction.BigFractionField
-
Get the multiplicative identity of the field.
- getOne() - Method in class org.apache.commons.math.fraction.FractionField
-
Get the multiplicative identity of the field.
- getOne() - Method in class org.apache.commons.math.util.BigRealField
-
Get the multiplicative identity of the field.
- getOneWayAnova() - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0
- getOptima() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Get all the optima found during the last call to
optimize
.
- getOptima() - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Get all the optima found during the last call to
optimize
.
- getOptima() - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Get all the optima found during the last call to
optimize
.
- getOptima() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get all the optima found during the last call to
optimize
.
- getOptimaValues() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get all the function values at optima found during the last call to
optimize
.
- getOrder() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
-
Get the order of the method.
- getOrder() - Method in class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
-
Get the order of the method.
- getOrder() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Get the order of the method.
- getOrder() - Method in class org.apache.commons.math.ode.nonstiff.HighamHall54Integrator
-
Get the order of the method.
- getP() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Returns the P rows permutation matrix.
- getP() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Returns the P rows permutation matrix.
- getP() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Returns the P rows permutation matrix.
- getP() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Returns the P rows permutation matrix.
- getParametersDimension() - Method in interface org.apache.commons.math.ode.jacobians.ODEWithJacobians
-
Deprecated.
Get the number of parameters.
- getParametersDimension() - Method in interface org.apache.commons.math.ode.jacobians.ParameterizedODE
-
Deprecated.
Get the number of parameters.
- getPartial(EstimatedParameter) - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
- getPattern() - Method in exception org.apache.commons.math.MathException
-
- getPattern() - Method in exception org.apache.commons.math.MathRuntimeException
-
- getPct(Object) - Method in class org.apache.commons.math.stat.Frequency
-
- getPct(Comparable<?>) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the percentage of values that are equal to v
(as a proportion between 0 and 1).
- getPct(int) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the percentage of values that are equal to v
(as a proportion between 0 and 1).
- getPct(long) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the percentage of values that are equal to v
(as a proportion between 0 and 1).
- getPct(char) - Method in class org.apache.commons.math.stat.Frequency
-
Returns the percentage of values that are equal to v
(as a proportion between 0 and 1).
- getPercentile(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns an estimate for the pth percentile of the stored values.
- getPercentileImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured percentile implementation.
- getPermutation() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the permutation associated with the lu decomposition.
- getPhase() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
-
Get the phase φ.
- getPi() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant π.
- getPiSplit() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant π split in two pieces.
- getPivot() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Returns the pivot permutation vector.
- getPivot() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Returns the pivot permutation vector.
- getPivot() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Returns the pivot permutation vector.
- getPivot() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Returns the pivot permutation vector.
- getPoint() - Method in class org.apache.commons.math.optimization.RealPointValuePair
-
Get the point.
- getPoint() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Get the point.
- getPoint() - Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
-
Get the n-dimensional point in integer space.
- getPointRef() - Method in class org.apache.commons.math.optimization.RealPointValuePair
-
Get a reference to the point.
- getPointRef() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Get a reference to the point.
- getPoints() - Method in class org.apache.commons.math.stat.clustering.Cluster
-
Get the points contained in the cluster.
- getPolynomialFunction() - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
as of 2.0 the function is not stored anymore within the instance.
- getPolynomials() - Method in class org.apache.commons.math.analysis.polynomials.PolynomialSplineFunction
-
Returns a copy of the interpolating polynomials array.
- getPopulationLimit() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Access the maximum population size.
- getPopulationLimit() - Method in interface org.apache.commons.math.genetics.Population
-
Access the maximum population size.
- getPopulationSize() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
Access the population size.
- getPopulationSize() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the population size.
- getPopulationSize() - Method in class org.apache.commons.math.genetics.ListPopulation
-
Access the current population size.
- getPopulationSize() - Method in interface org.apache.commons.math.genetics.Population
-
Access the current population size.
- getPrefix() - Method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the format prefix.
- getPrefix() - Method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the format prefix.
- getPrevious() - Method in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
- getPreviousTime() - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Get the previous grid point time.
- getPreviousTime() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Get the previous soft grid point time.
- getPreviousTime() - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Get the previous grid point time.
- getProbabilityOfSuccess() - Method in interface org.apache.commons.math.distribution.BinomialDistribution
-
Access the probability of success for this distribution.
- getProbabilityOfSuccess() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Access the probability of success for this distribution.
- getProbabilityOfSuccess() - Method in interface org.apache.commons.math.distribution.PascalDistribution
-
Access the probability of success for this distribution.
- getProbabilityOfSuccess() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Access the probability of success for this distribution.
- getProperInstance() - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Returns the default complex format for the current locale.
- getProperInstance(Locale) - Static method in class org.apache.commons.math.fraction.BigFractionFormat
-
Returns the default complex format for the given locale.
- getProperInstance() - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Returns the default complex format for the current locale.
- getProperInstance(Locale) - Static method in class org.apache.commons.math.fraction.FractionFormat
-
Returns the default complex format for the given locale.
- getPulsation() - Method in class org.apache.commons.math.optimization.fitting.HarmonicFunction
-
Get the pulsation ω.
- getQ() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Returns the matrix Q of the decomposition.
- getQ() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Returns the matrix Q of the decomposition.
- getQ0() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the scalar coordinate of the quaternion.
- getQ1() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the first coordinate of the vectorial part of the quaternion.
- getQ2() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the second coordinate of the vectorial part of the quaternion.
- getQ3() - Method in class org.apache.commons.math.geometry.Rotation
-
Get the third coordinate of the vectorial part of the quaternion.
- getQT() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Returns the transpose of the matrix Q of the decomposition.
- getQT() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Returns the transpose of the matrix Q of the decomposition.
- getQuantile() - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Returns the value of the quantile field (determines what percentile is
computed when evaluate() is called with no quantile argument).
- getR() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Returns the matrix R of the decomposition.
- getR() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Returns the matrix R of the decomposition.
- getR() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getRadixDigits() - Method in class org.apache.commons.math.dfp.Dfp
-
Get the number of radix digits of the instance.
- getRadixDigits() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the number of radix digits of the
Dfp
instances built by this factory.
- getRandomGenerator() - Static method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the (static) random generator.
- getRank() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Return the effective numerical matrix rank.
- getRank() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Return the effective numerical matrix rank.
- getRank() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Get the rank of the covariance matrix.
- getRankCorrelation() - Method in class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
- getReal() - Method in class org.apache.commons.math.complex.Complex
-
Access the real part.
- getRealEigenvalue(int) - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the real part of the ith eigenvalue of the original matrix.
- getRealEigenvalue(int) - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the real part of the ith eigenvalue of the original matrix.
- getRealEigenvalues() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns a copy of the real parts of the eigenvalues of the original matrix.
- getRealEigenvalues() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns a copy of the real parts of the eigenvalues of the original matrix.
- getRealFormat() - Method in class org.apache.commons.math.complex.ComplexFormat
-
Access the realFormat.
- getReducedFraction(int, int) - Static method in class org.apache.commons.math.fraction.BigFraction
-
Creates a BigFraction
instance with the 2 parts of a fraction
Y/Z.
- getReducedFraction(int, int) - Static method in class org.apache.commons.math.fraction.Fraction
-
Creates a Fraction
instance with the 2 parts
of a fraction Y/Z.
- getRegressionSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of squared deviations of the predicted y values about
their mean (which equals the mean of y).
- getRelationship() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
-
Get the relationship between left and right hand sides.
- getRelativeAccuracy() - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Get the actual relative accuracy.
- getRelativeAccuracy() - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Get the actual relative accuracy.
- getRelativeAccuracy() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the actual relative accuracy.
- getRepresentation() - Method in class org.apache.commons.math.genetics.AbstractListChromosome
-
Returns the (immutable) inner representation of the chromosome.
- getResidual() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Get the residual for this measurement
The residual is the measured value minus the theoretical value.
- getResult() - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
-
Get the result of the last run of the integrator.
- getResult() - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Access the last computed integral.
- getResult() - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Get the result of the last run of the solver.
- getResult() - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Get the result of the last run of the solver.
- getResult() - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getResult() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getResult() - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Get the result of the last run of the optimizer.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Returns the value of the statistic based on the values that have been added.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialCovariance
-
Get the covariance matrix.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.VectorialMean
-
Get the mean vector.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
-
Returns the current value of the Statistic.
- getResult() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Returns the current value of the Statistic.
- getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Returns the current value of the Statistic.
- getRMS(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Get the Root Mean Square value.
- getRMS(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
-
Deprecated.
Get the Root Mean Square value.
- getRMS() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Get the Root Mean Square value.
- getRootMatrix() - Method in class org.apache.commons.math.random.CorrelatedRandomVectorGenerator
-
Get the root of the covariance matrix.
- getRoundingMode() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the current rounding mode.
- getRoundingMode() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Gets the rounding mode
- getRoundingMode() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
- getRoundingMode() - Method in class org.apache.commons.math.util.BigReal
-
Gets the rounding mode for division operations
The default is RoundingMode.HALF_UP
- getRow(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in row number row
as an array.
- getRow(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in row number row
as an array.
- getRow(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in row number row
as an array.
- getRow(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in row number row
as an array.
- getRow(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in row number row
as an array.
- getRow(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in row number row
as an array.
- getRow(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in row number row
as an array.
- getRow(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in row number row
as an array.
- getRowAsDoubleArray(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in row number row
as an array
of double values.
- getRowAsDoubleArray(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in row number row
as an array
of double values.
- getRowDimension() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in interface org.apache.commons.math.linear.AnyMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Returns the number of rows in the matrix.
- getRowDimension() - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Returns the number of rows in the matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowMatrix(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in row number row
as a row matrix.
- getRowVector(int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the entries in row number row
as a vector.
- getRowVector(int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the entries in row number row
as a vector.
- getRSquare() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getS() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the diagonal matrix Σ of the decomposition.
- getS() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the diagonal matrix Σ of the decomposition.
- getSafety() - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Get the safety factor for stepsize control.
- getSafety() - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Get the safety factor for stepsize control.
- getSampleSize() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
Access the sample size.
- getSampleSize() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Access the sample size.
- getSampleStats() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
- getSampleStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
- getScale() - Method in interface org.apache.commons.math.distribution.CauchyDistribution
-
Access the scale parameter.
- getScale() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Access the scale parameter.
- getScale() - Method in interface org.apache.commons.math.distribution.WeibullDistribution
-
Access the scale parameter.
- getScale() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the scale parameter.
- getScale() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Sets the scale for division operations.
- getScale() - Method in class org.apache.commons.math.util.BigReal
-
Sets the scale for division operations.
- getSecond() - Method in class org.apache.commons.math.genetics.ChromosomePair
-
Access the second chromosome.
- getSecondMoment() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns a statistic related to the Second Central Moment.
- getSecondMoment() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns a statistic related to the Second Central Moment.
- getSelectionPolicy() - Method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Returns the selection policy.
- getSeparator() - Method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the format separator between components.
- getSeparator() - Method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the format separator between components.
- getShape() - Method in interface org.apache.commons.math.distribution.WeibullDistribution
-
Access the shape parameter.
- getShape() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Access the shape parameter.
- getSigma() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for property sigma.
- getSignificance() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the significance level of the slope (equiv) correlation.
- getSingularValues() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the diagonal elements of the matrix Σ of the decomposition.
- getSingularValues() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the diagonal elements of the matrix Σ of the decomposition.
- getSize() - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Get the total number of elements.
- getSizes() - Method in class org.apache.commons.math.util.MultidimensionalCounter
-
Get the number of multidimensional counter slots in each dimension.
- getSkewness() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the skewness of the available values.
- getSkewnessImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured skewness implementation.
- getSlope() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the slope of the estimated regression line.
- getSlopeConfidenceInterval() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the half-width of a 95% confidence interval for the slope
estimate.
- getSlopeConfidenceInterval(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the half-width of a (100-100*alpha)% confidence interval for
the slope estimate.
- getSlopeStdErr() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getSolver() - Method in interface org.apache.commons.math.linear.CholeskyDecomposition
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in class org.apache.commons.math.linear.CholeskyDecompositionImpl
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Get a solver for finding the A × X = B solution in exact linear sense.
- getSolver() - Method in interface org.apache.commons.math.linear.QRDecomposition
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in class org.apache.commons.math.linear.QRDecompositionImpl
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolver() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Get a solver for finding the A × X = B solution in least square sense.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Returns the solver absolute accuracy for inverse cumulative computation.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Return the absolute accuracy setting of the solver used to estimate
inverse cumulative probabilities.
- getSortedValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the current set of values in an array of double primitives,
sorted in ascending order.
- getSourceString() - Method in class org.apache.commons.math.exception.util.DummyLocalizable
-
Get the source (non-localized) string.
- getSourceString() - Method in interface org.apache.commons.math.exception.util.Localizable
-
Get the source (non-localized) string.
- getSourceString() - Method in enum org.apache.commons.math.exception.util.LocalizedFormats
-
Get the source (non-localized) string.
- getSparcity() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
- getSparsity() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
- getSpecificPattern() - Method in exception org.apache.commons.math.exception.MathIllegalArgumentException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in exception org.apache.commons.math.exception.MathIllegalStateException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in interface org.apache.commons.math.exception.MathThrowable
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in exception org.apache.commons.math.exception.MathUnsupportedOperationException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in exception org.apache.commons.math.MathException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSpecificPattern() - Method in exception org.apache.commons.math.MathRuntimeException
-
Gets the localizable pattern used to build the specific part of the message of this throwable.
- getSqr2() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √2.
- getSqr2Reciprocal() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √2 / 2.
- getSqr2Split() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √2 split in two pieces.
- getSqr3() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √3.
- getSqr3Reciprocal() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant √3 / 3.
- getStandardDeviation() - Method in interface org.apache.commons.math.distribution.NormalDistribution
-
Access the standard deviation.
- getStandardDeviation() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Access the standard deviation.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the standard deviation of the available values.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the standard deviation of the available values.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getStandardDeviation() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
standard deviation of the ith entries of the arrays
that correspond to each multivariate sample
- getStandardDeviation() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the standard deviation of the available values.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the standard deviation of the values that have been added.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the standard deviation of the available values.
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the standard deviation of the values that have been added.
- getStarterIntegrator() - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Get the starter integrator.
- getStartValue() - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
- getStepHandlers() - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Get all the step handlers that have been added to the integrator.
- getStepHandlers() - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Get all the step handlers that have been added to the integrator.
- getStepHandlers() - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Get all the step handlers that have been added to the integrator.
- getStrict() - Method in exception org.apache.commons.math.exception.NonMonotonousSequenceException
-
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Gets a submatrix.
- getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Gets a submatrix.
- getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Gets a submatrix.
- getSubVector(int, int) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in interface org.apache.commons.math.linear.FieldVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in interface org.apache.commons.math.linear.RealVector
-
Get a subvector from consecutive elements.
- getSubVector(int, int) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Get a subvector from consecutive elements.
- getSuffix() - Method in class org.apache.commons.math.geometry.Vector3DFormat
-
Get the format suffix.
- getSuffix() - Method in class org.apache.commons.math.linear.RealVectorFormat
-
Get the format suffix.
- getSum() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the sum of the values that have been added to Univariate.
- getSum() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the sum of the values that have been added to Univariate.
- getSum() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getSum() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
sum of the ith entries of the arrays
that correspond to each multivariate sample
- getSum() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the sum of the values that have been added to Univariate.
- getSum() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getSum() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the sum of the values that have been added
- getSum() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getSum() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the sum of the values that have been added
- getSumFreq() - Method in class org.apache.commons.math.stat.Frequency
-
Returns the sum of all frequencies.
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured sum implementation.
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured Sum implementation
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured Sum implementation
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured Sum implementation
- getSumImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured Sum implementation
- getSumLog() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getSumLog() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
sum of logs of the ith entries of the arrays
that correspond to each multivariate sample
- getSumLog() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Returns the currently configured sum of logs implementation
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured sum of logs implementation
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured sum of logs implementation
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured sum of logs implementation
- getSumLogImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured sum of logs implementation
- getSummary() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
- getSummary() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
- getSummary() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
- getSumOfCrossProducts() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of crossproducts, xi*yi.
- getSumOfLogs() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the sum of the logs of all the aggregated data.
- getSumOfLogs() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the sum of the logs of the values that have been added.
- getSumsq() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the sum of the squares of all the aggregated data.
- getSumsq() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the sum of the squares of the available values.
- getSumSq() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
- getSumSq() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalMultivariateSummary
-
Returns an array whose ith entry is the
sum of squares of the ith entries of the arrays
that correspond to each multivariate sample
- getSumsq() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the sum of the squares of the values that have been added.
- getSumSq() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
- getSumsq() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the sum of the squares of the values that have been added.
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured sum of squares implementation.
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Returns the currently configured sum of squares implementation
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured sum of squares implementation
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Returns the currently configured sum of squares implementation
- getSumsqImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured sum of squares implementation
- getSumSquaredErrors() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Returns the lower bound of the support for this distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Returns the lower bound of the support for this distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Returns the lower bound for the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportLowerBound() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Returns the lower bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Returns the upper bound of the support for this distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Returns the upper bound of the support for this distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Returns the upper bound for the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Returns the upper bound for the support of the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getSupportUpperBound() - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Returns the upper bound of the support for the distribution.
- getTheoreticalValue() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Get the theoretical value expected for this measurement
- getTiesStrategy() - Method in class org.apache.commons.math.stat.ranking.NaturalRanking
-
Return the TiesStrategy
- getTotalSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of squared deviations of the y values about their mean.
- getTrace() - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTrace() - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the
trace of the matrix (the sum of the elements on the main diagonal).
- getTransformer(Class<?>) - Method in class org.apache.commons.math.util.TransformerMap
-
Returns the Transformer that is mapped to a class
if mapping is not present, this returns null.
- getTTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0
- getTwo() - Method in class org.apache.commons.math.dfp.Dfp
-
Get the constant 2.
- getTwo() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant 2.
- getU() - Method in interface org.apache.commons.math.linear.FieldLUDecomposition
-
Returns the matrix U of the decomposition.
- getU() - Method in class org.apache.commons.math.linear.FieldLUDecompositionImpl
-
Returns the matrix U of the decomposition.
- getU() - Method in interface org.apache.commons.math.linear.LUDecomposition
-
Returns the matrix U of the decomposition.
- getU() - Method in class org.apache.commons.math.linear.LUDecompositionImpl
-
Returns the matrix U of the decomposition.
- getU() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the matrix U of the decomposition.
- getU() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the matrix U of the decomposition.
- getUnboundParameters() - Method in interface org.apache.commons.math.estimation.EstimationProblem
-
Deprecated.
Get the unbound parameters of the problem.
- getUnboundParameters() - Method in class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Get the unbound parameters of the problem.
- getUniqueCount() - Method in class org.apache.commons.math.stat.Frequency
-
Returns the number of values in the frequency table.
- getUnknownDistributionChiSquareTest() - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0
- getUpperBounds() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
-
Returns the array of upper bounds for the bins.
- getUpperBounds() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
-
Returns a fresh copy of the array of upper bounds for the bins.
- getUT() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the transpose of the matrix U of the decomposition.
- getUT() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the transpose of the matrix U of the decomposition.
- getV() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the matrix V of the decomposition.
- getV() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the matrix V of the decomposition.
- getV() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the matrix V of the decomposition.
- getV() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the matrix V of the decomposition.
- getValue() - Method in class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
-
Get the value of the entry.
- getValue() - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
-
Get the value of the entry.
- getValue() - Method in class org.apache.commons.math.linear.RealVector.Entry
-
Get the value of the entry.
- getValue() - Method in class org.apache.commons.math.optimization.linear.LinearConstraint
-
Get the value of the constraint (right hand side).
- getValue(double[]) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Compute the value of the linear equation at the current point
- getValue(RealVector) - Method in class org.apache.commons.math.optimization.linear.LinearObjectiveFunction
-
Compute the value of the linear equation at the current point
- getValue() - Method in class org.apache.commons.math.optimization.RealPointValuePair
-
Get the value of the objective function.
- getValue() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Get the value of the objective function.
- getValueRef() - Method in class org.apache.commons.math.optimization.VectorialPointValuePair
-
Get a reference to the value of the objective function.
- getValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the current set of values in an array of double primitives.
- getValues() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the current set of values in an array of double primitives.
- getValues() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
- getValuesFileURL() - Method in class org.apache.commons.math.random.ValueServer
-
Getter for valuesFileURL
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
-
Returns the variance of the available values.
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the variance of the available values.
- getVariance() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
-
Returns the variance of the available values.
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the variance of the values that have been added.
- getVariance() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the variance of the values that have been added.
- getVarianceDirection() - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Returns the varianceDirection property.
- getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the currently configured variance implementation.
- getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Returns the currently configured variance implementation
- getVarianceImpl() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Returns the currently configured variance implementation
- getVT() - Method in interface org.apache.commons.math.linear.EigenDecomposition
-
Returns the transpose of the matrix V of the decomposition.
- getVT() - Method in class org.apache.commons.math.linear.EigenDecompositionImpl
-
Returns the transpose of the matrix V of the decomposition.
- getVT() - Method in interface org.apache.commons.math.linear.SingularValueDecomposition
-
Returns the transpose of the matrix V of the decomposition.
- getVT() - Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Returns the transpose of the matrix V of the decomposition.
- getWeight() - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Get the weight of the measurement in the least squares problem
- getWeight() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
-
Get the weight of the measurement in the fitting process.
- getWholeFormat() - Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
-
Access the whole format.
- getWholeFormat() - Method in class org.apache.commons.math.fraction.ProperFractionFormat
-
Access the whole format.
- getWindowSize() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Returns the maximum number of values that can be stored in the
dataset, or INFINITE_WINDOW (-1) if there is no limit.
- getWindowSize() - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Returns the maximum number of values that can be stored in the
dataset, or INFINITE_WINDOW (-1) if there is no limit.
- getX() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the abscissa of the vector.
- getX() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
-
Get the abscissa of the point.
- getXSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Returns the sum of squared deviations of the x values about their mean.
- getY() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the ordinate of the vector.
- getY() - Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
-
Get the observed value of the function at x.
- getZ() - Method in class org.apache.commons.math.geometry.Vector3D
-
Get the height of the vector.
- getZero() - Method in class org.apache.commons.math.complex.ComplexField
-
Get the additive identity of the field.
- getZero() - Method in class org.apache.commons.math.dfp.Dfp
-
Get the constant 0.
- getZero() - Method in class org.apache.commons.math.dfp.DfpField
-
Get the constant 0.
- getZero() - Method in interface org.apache.commons.math.Field
-
Get the additive identity of the field.
- getZero() - Method in class org.apache.commons.math.fraction.BigFractionField
-
Get the additive identity of the field.
- getZero() - Method in class org.apache.commons.math.fraction.FractionField
-
Get the additive identity of the field.
- getZero() - Method in class org.apache.commons.math.util.BigRealField
-
Get the additive identity of the field.
- GillIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements the Gill fourth order Runge-Kutta
integrator for Ordinary Differential Equations .
- GillIntegrator(double) - Constructor for class org.apache.commons.math.ode.nonstiff.GillIntegrator
-
Simple constructor.
- GLSMultipleLinearRegression - Class in org.apache.commons.math.stat.regression
-
The GLS implementation of the multiple linear regression.
- GLSMultipleLinearRegression() - Constructor for class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
- goal - Variable in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Deprecated.
- goal - Variable in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
- GoalType - Enum in org.apache.commons.math.optimization
-
Goal type for an optimization problem.
- gradient() - Method in interface org.apache.commons.math.analysis.DifferentiableMultivariateRealFunction
-
Returns the gradient function.
- gradient(double, double[]) - Method in class org.apache.commons.math.optimization.fitting.ParametricGaussianFunction
-
Computes the gradient vector for a four variable version of the function
where the parameters, a, b, c, and d,
are considered the variables, not x.
- gradient(double, double[]) - Method in interface org.apache.commons.math.optimization.fitting.ParametricRealFunction
-
Compute the gradient of the function with respect to its parameters.
- GraggBulirschStoerIntegrator - Class in org.apache.commons.math.ode.nonstiff
-
This class implements a Gragg-Bulirsch-Stoer integrator for
Ordinary Differential Equations.
- GraggBulirschStoerIntegrator(double, double, double, double) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Simple constructor.
- GraggBulirschStoerIntegrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Simple constructor.
- greaterThan(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Check if instance is greater than x.
- guess() - Method in class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
-
Guesses the parameters based on the observed points.
- guess() - Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
-
Estimate a first guess of the coefficients.
- guessParametersErrors(EstimationProblem) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Guess the errors in unbound estimated parameters.
- guessParametersErrors(EstimationProblem) - Method in interface org.apache.commons.math.estimation.Estimator
-
Deprecated.
Guess the errors in estimated parameters.
- guessParametersErrors() - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Guess the errors in optimized parameters.
- SAFE_MIN - Static variable in class org.apache.commons.math.util.MathUtils
-
Safe minimum, such that 1 / SAFE_MIN does not overflow.
- safeNorm(double[]) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the Cartesian norm (2-norm), handling both overflow and underflow.
- sample() - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Generates a random value sampled from this distribution.
- sample(int) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
-
Generates a random sample from the distribution.
- sample() - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Generates a random value sampled from this distribution.
- sample(int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
-
Generates a random sample from the distribution.
- sample() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Generates a random value sampled from this distribution.
- sample() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Generates a random value sampled from this distribution.
- sample() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Generates a random value sampled from this distribution.
- sample(UnivariateRealFunction, double, double, int) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
-
Sample the given univariate real function on the given interval.
- sanityChecks(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Perform some sanity checks on the integration parameters.
- sanityChecks(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Perform some sanity checks on the integration parameters.
- scalAbsoluteTolerance - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Allowed absolute scalar error.
- scalarAdd(T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(BigDecimal) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the result of adding d to each entry of this.
- scalarAdd(BigDecimal) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the result of adding d to each entry of this.
- scalarAdd(T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the result of adding d to each entry of this.
- scalarAdd(double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the result of adding d to each entry of this.
- scalarMultiply(double) - Method in class org.apache.commons.math.geometry.Vector3D
-
Multiply the instance by a scalar
- scalarMultiply(T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(BigDecimal) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the result multiplying each entry of this by d.
- scalarMultiply(BigDecimal) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns the result of multiplying each entry of this by d
- scalarMultiply(T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Returns the result multiplying each entry of this by d.
- scalarMultiply(double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Returns the result multiplying each entry of this by d.
- scalb(double, int) - Static method in class org.apache.commons.math.util.FastMath
-
Multiply a double number by a power of 2.
- scalb(float, int) - Static method in class org.apache.commons.math.util.FastMath
-
Multiply a float number by a power of 2.
- scalb(double, int) - Static method in class org.apache.commons.math.util.MathUtils
-
- scaleArray(double[], double) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
-
Multiply every component in the given real array by the
given real number.
- scaleArray(Complex[], double) - Static method in class org.apache.commons.math.transform.FastFourierTransformer
-
Multiply every component in the given complex array by the
given real number.
- scaled - Variable in class org.apache.commons.math.ode.MultistepIntegrator
-
First scaled derivative (h y').
- scalRelativeTolerance - Variable in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Allowed relative scalar error.
- search(UnivariateRealFunction, GoalType, double, double) - Method in class org.apache.commons.math.optimization.univariate.BracketFinder
-
Search new points that bracket a local optimum of the function.
- searchForFitnessUpdate(Population) - Method in class org.apache.commons.math.genetics.Chromosome
-
Searches the population for a chromosome representing the same solution,
and if it finds one, updates the fitness to its value.
- SecantSolver - Class in org.apache.commons.math.analysis.solvers
-
Implements a modified version of the
secant method
for approximating a zero of a real univariate function.
- SecantSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.solvers.SecantSolver
-
- SecantSolver() - Constructor for class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- SecondMoment - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes a statistic related to the Second Central Moment.
- SecondMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Create a SecondMoment instance
- SecondMoment(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SecondMoment
-
Copy constructor, creates a new SecondMoment
identical
to the original
- secondMoment - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
SecondMoment is used to compute the mean and variance
- SecondOrderDifferentialEquations - Interface in org.apache.commons.math.ode
-
This interface represents a second order differential equations set.
- SecondOrderIntegrator - Interface in org.apache.commons.math.ode
-
This interface represents a second order integrator for
differential equations.
- select(Population) - Method in interface org.apache.commons.math.genetics.SelectionPolicy
-
Select two chromosomes from the population.
- select(Population) - Method in class org.apache.commons.math.genetics.TournamentSelection
-
Select two chromosomes from the population.
- SelectionPolicy - Interface in org.apache.commons.math.genetics
-
Algorithm used to select a chromosome pair from a population.
- SemiVariance - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes the semivariance of a set of values with respect to a given cutoff value.
- SemiVariance() - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Constructs a SemiVariance with default (true) biasCorrected
property and default (Downside) varianceDirection
property.
- SemiVariance(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Constructs a SemiVariance with the specified biasCorrected
property and default (Downside) varianceDirection
property.
- SemiVariance(SemiVariance.Direction) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Constructs a SemiVariance with the specified Direction
property
and default (true) biasCorrected
property
- SemiVariance(boolean, SemiVariance.Direction) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Constructs a SemiVariance with the specified isBiasCorrected
property and the specified Direction
property.
- SemiVariance(SemiVariance) - Constructor for class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Copy constructor, creates a new SemiVariance
identical
to the original
- SemiVariance.Direction - Enum in org.apache.commons.math.stat.descriptive.moment
-
The direction of the semivariance - either upside or downside.
- serializeRealMatrix(RealMatrix, ObjectOutputStream) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- serializeRealVector(RealVector, ObjectOutputStream) - Static method in class org.apache.commons.math.linear.MatrixUtils
-
- set(double) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Set all elements to a single value.
- set(int, ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set a set of consecutive elements.
- set(T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set all elements to a single value.
- set(int, ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set a set of consecutive elements.
- set(double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set all elements to a single value.
- set(T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Set all elements to a single value.
- set(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Set all elements to a single value.
- set(double) - Method in interface org.apache.commons.math.linear.RealVector
-
Set all elements to a single value.
- set(T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Set all elements to a single value.
- setAbsoluteAccuracy(double) - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Set the absolute accuracy.
- setAbsoluteAccuracy(double) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Set the absolute accuracy.
- setAbsoluteAccuracy(double) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Set the absolute accuracy.
- setAlpha(double) - Method in interface org.apache.commons.math.distribution.BetaDistribution
-
- setAlpha(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setAlpha(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
-
- setAlpha(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setArity(int) - Method in class org.apache.commons.math.genetics.TournamentSelection
-
Sets the arity (number of chromosomes drawn to the tournament).
- setBeta(double) - Method in interface org.apache.commons.math.distribution.BetaDistribution
-
- setBeta(double) - Method in class org.apache.commons.math.distribution.BetaDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setBeta(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
-
- setBeta(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Sets the biasCorrected property.
- setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
- setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
-
- setBound(boolean) - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Set the bound flag of the parameter
- setBrightnessExponent(int) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
-
Set the brightness exponent.
- setChiSquareTest(TTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0 - not compatible with use from multiple threads
- setChiSquareTest(ChiSquareTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0 - not compatible with use from multiple threads
- setChromosomes(List<Chromosome>) - Method in class org.apache.commons.math.genetics.ListPopulation
-
Sets the list of chromosomes.
- setColumn(int, T[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, T[]) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, double[]) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, T[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumn(int, double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnMatrix(int, RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in column number column
as a column matrix.
- setColumnVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, RealVector) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in column number column
as a vector.
- setColumnVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in column number column
as a vector.
- setContractionCriteria(float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the contraction criteria for this ExpandContractDoubleArray.
- setConvergence(double) - Method in class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Set the convergence criterion threshold.
- setConvergenceChecker(RealConvergenceChecker) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Set the convergence checker.
- setConvergenceChecker(VectorialConvergenceChecker) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set the convergence checker.
- setConvergenceChecker(VectorialConvergenceChecker) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Set the convergence checker.
- setConvergenceChecker(VectorialConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Set the convergence checker.
- setConvergenceChecker(RealConvergenceChecker) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Set the convergence checker.
- setCostRelativeTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Set the desired relative error in the sum of squares.
- setCostRelativeTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the desired relative error in the sum of squares.
- setData(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Set the data array.
- setData(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
-
Set the data array.
- setData(double[]) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Set the data array.
- setData(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Set the data array.
- setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
-
- setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.TDistribution
-
- setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setDenominatorDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.FDistribution
-
- setDenominatorDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setDenominatorFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.AbstractFormat
-
Modify the denominator format.
- setDistribution(ChiSquaredDistribution) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
-
Modify the distribution used to compute inference statistics.
- setDistribution(TDistribution) - Method in class org.apache.commons.math.stat.inference.TTestImpl
-
Deprecated.
in 2.2 (to be removed in 3.0).
- setDistribution(TDistribution) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
-
Deprecated.
in 2.2 (to be removed in 3.0).
- setElement(int, double) - Method in interface org.apache.commons.math.util.DoubleArray
-
Sets the element at the specified index.
- setElement(int, double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the element at the specified index.
- setElitismRate(double) - Method in class org.apache.commons.math.genetics.ElitisticListPopulation
-
Sets the elitism rate, i.e.
- setEntry(int, int, T) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, T) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, T) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set a single element.
- setEntry(int, double) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set a single element.
- setEntry(int, int, T) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, T) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, T) - Method in interface org.apache.commons.math.linear.FieldVector
-
Set a single element.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, double) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Set a single element.
- setEntry(int, int, double) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Set the entry in the specified row and column.
- setEntry(int, int, double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Set the entry in the specified row and column.
- setEntry(int, double) - Method in interface org.apache.commons.math.linear.RealVector
-
Set a single element.
- setEntry(int, int, T) - Method in class org.apache.commons.math.linear.SparseFieldMatrix
-
Set the entry in the specified row and column.
- setEntry(int, T) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Set a single element.
- setEquations(FirstOrderDifferentialEquations) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Set the differential equations.
- setEstimate(double) - Method in class org.apache.commons.math.estimation.EstimatedParameter
-
Deprecated.
Set a new estimated value for the parameter.
- setExpansionFactor(float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the expansionFactor.
- setExpansionMode(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the expansionMode
.
- setExponent(double) - Method in interface org.apache.commons.math.distribution.ZipfDistribution
-
- setExponent(double) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setFunctionValue(double) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Set the value at the optimum.
- setFunctionValueAccuracy(double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Set the function value accuracy.
- setFunctionValueAccuracy(double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Set the function value accuracy.
- setGamma(GammaDistribution) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setGeoMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the geometric mean.
- setGeoMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the geometric mean.
- setGeoMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the geometric mean.
- setGeoMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the geometric mean.
- setGeometricMeanImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the gemoetric mean.
- setIEEEFlags(int) - Method in class org.apache.commons.math.dfp.DfpField
-
Sets the IEEE 854 status flags.
- setIEEEFlagsBits(int) - Method in class org.apache.commons.math.dfp.DfpField
-
Sets some bits in the IEEE 854 status flags, without changing the already set bits.
- setIgnored(boolean) - Method in class org.apache.commons.math.estimation.WeightedMeasurement
-
Deprecated.
Set the ignore flag to the specified value
Setting the ignore flag to true allow to reject wrong
measurements, which sometimes can be detected only rather late.
- setImaginaryCharacter(String) - Method in class org.apache.commons.math.complex.ComplexFormat
-
Modify the imaginaryCharacter.
- setImaginaryFormat(NumberFormat) - Method in class org.apache.commons.math.complex.ComplexFormat
-
Modify the imaginaryFormat.
- setIndex(int) - Method in class org.apache.commons.math.linear.RealVector.Entry
-
Set the index of the entry.
- setInitialCapacity(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Sets the initial capacity.
- setInitialStep(double) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
Set the initial step used to bracket the optimum in line search.
- setInitialStepBoundFactor(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Set the positive input variable used in determining the initial step bound.
- setInitialStepBoundFactor(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the positive input variable used in determining the initial step bound.
- setInitialStepSize(double) - Method in class org.apache.commons.math.ode.nonstiff.AdaptiveStepsizeIntegrator
-
Set the initial step size.
- setInterpolatedTime(double) - Method in class org.apache.commons.math.ode.ContinuousOutputModel
-
Set the time of the interpolated point.
- setInterpolatedTime(double) - Method in interface org.apache.commons.math.ode.jacobians.StepInterpolatorWithJacobians
-
Deprecated.
Set the time of the interpolated point.
- setInterpolatedTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Set the time of the interpolated point.
- setInterpolatedTime(double) - Method in interface org.apache.commons.math.ode.sampling.StepInterpolator
-
Set the time of the interpolated point.
- setInterpolationControl(boolean, int) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Set the interpolation order control parameter.
- setKurtosisImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the kurtosis.
- setLineSearchSolver(UnivariateRealSolver) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
Set the solver to use during line search.
- setMaxCostEval(int) - Method in class org.apache.commons.math.estimation.AbstractEstimator
-
Deprecated.
Set the maximal number of cost evaluations allowed.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Set the maximal number of differential equations function evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.ode.jacobians.FirstOrderIntegratorWithJacobians
-
Deprecated.
Set the maximal number of differential equations function evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.ode.ODEIntegrator
-
Set the maximal number of differential equations function evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxEvaluations(int) - Method in interface org.apache.commons.math.optimization.UnivariateRealOptimizer
-
Set the maximal number of functions evaluations.
- setMaxGrowth(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Set the maximal growth factor for stepsize control.
- setMaxGrowth(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Set the maximal growth factor for stepsize control.
- setMaximalIterationCount(int) - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Set the upper limit for the number of iterations.
- setMaximalIterationCount(int) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Set the upper limit for the number of iterations.
- setMaximalIterationCount(int) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Set the upper limit for the number of iterations.
- setMaxImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the maximum.
- setMaxImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the maximum.
- setMaxImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the maximum.
- setMaxImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the maximum.
- setMaxImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the maximum.
- setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateRealOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.DifferentiableMultivariateVectorialOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.general.AbstractScalarDifferentiableOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.linear.AbstractLinearOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.linear.LinearOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in class org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMaxIterations(int) - Method in interface org.apache.commons.math.optimization.MultivariateRealOptimizer
-
Set the maximal number of iterations of the algorithm.
- setMean(double) - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
-
- setMean(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setMean(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
-
- setMean(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setMean(double) - Method in interface org.apache.commons.math.distribution.PoissonDistribution
-
- setMean(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setMeanImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the mean.
- setMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the mean.
- setMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the mean.
- setMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the mean.
- setMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the mean.
- setMedian(double) - Method in interface org.apache.commons.math.distribution.CauchyDistribution
-
- setMedian(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setMicropshereElements(int) - Method in class org.apache.commons.math.analysis.interpolation.MicrosphereInterpolator
-
Set the number of microsphere elements.
- setMinimalIterationCount(int) - Method in interface org.apache.commons.math.analysis.integration.UnivariateRealIntegrator
-
Set the lower limit for the number of iterations.
- setMinimalIterationCount(int) - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Set the lower limit for the number of iterations.
- setMinImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the minimum.
- setMinImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the minimum.
- setMinImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the minimum.
- setMinImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the minimum.
- setMinImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the minimum.
- setMinReduction(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Set the minimal reduction factor for stepsize control.
- setMinReduction(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Set the minimal reduction factor for stepsize control.
- setMode(int) - Method in class org.apache.commons.math.random.ValueServer
-
Setter for property mode.
- setMu(double) - Method in class org.apache.commons.math.random.ValueServer
-
Setter for property mu.
- setNoIntercept(boolean) - Method in class org.apache.commons.math.stat.regression.AbstractMultipleLinearRegression
-
- setNormal(NormalDistribution) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumberOfElements(int) - Method in interface org.apache.commons.math.distribution.ZipfDistribution
-
- setNumberOfElements(int) - Method in class org.apache.commons.math.distribution.ZipfDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumberOfSuccesses(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
- setNumberOfSuccesses(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumberOfSuccesses(int) - Method in interface org.apache.commons.math.distribution.PascalDistribution
-
- setNumberOfSuccesses(int) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumberOfTrials(int) - Method in interface org.apache.commons.math.distribution.BinomialDistribution
-
- setNumberOfTrials(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumElements(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
This function allows you to control the number of elements contained
in this array, and can be used to "throw out" the last n values in an
array.
- setNumeratorDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.FDistribution
-
- setNumeratorDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setNumeratorFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.AbstractFormat
-
Modify the numerator format.
- setOneWayAnova(OneWayAnova) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0 - not compatible with use from multiple threads
- setOrderControl(int, double, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Set the order control parameters.
- setOrthoTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Set the desired max cosine on the orthogonality.
- setOrthoTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the desired max cosine on the orthogonality.
- setParameter(int, double) - Method in interface org.apache.commons.math.ode.jacobians.ParameterizedODE
-
Deprecated.
Set a parameter.
- setParRelativeTolerance(double) - Method in class org.apache.commons.math.estimation.LevenbergMarquardtEstimator
-
Deprecated.
Set the desired relative error in the approximate solution parameters.
- setParRelativeTolerance(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the desired relative error in the approximate solution parameters.
- setPercentileImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
- setPopulationLimit(int) - Method in class org.apache.commons.math.genetics.ListPopulation
-
Sets the maximal population size.
- setPopulationSize(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
- setPopulationSize(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setPreconditioner(Preconditioner) - Method in class org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer
-
Set the preconditioner.
- setProbabilityOfSuccess(double) - Method in interface org.apache.commons.math.distribution.BinomialDistribution
-
- setProbabilityOfSuccess(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setProbabilityOfSuccess(double) - Method in interface org.apache.commons.math.distribution.PascalDistribution
-
- setProbabilityOfSuccess(double) - Method in class org.apache.commons.math.distribution.PascalDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setQRRankingThreshold(double) - Method in class org.apache.commons.math.optimization.general.LevenbergMarquardtOptimizer
-
Set the desired threshold for QR ranking.
- setQuantile(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
-
Sets the value of the quantile field (determines what percentile is
computed when evaluate() is called with no quantile argument).
- setRandomGenerator(RandomGenerator) - Static method in class org.apache.commons.math.genetics.GeneticAlgorithm
-
Set the (static) random generator.
- setRealFormat(NumberFormat) - Method in class org.apache.commons.math.complex.ComplexFormat
-
Modify the realFormat.
- setRelativeAccuracy(double) - Method in interface org.apache.commons.math.ConvergingAlgorithm
-
Deprecated.
Set the relative accuracy.
- setRelativeAccuracy(double) - Method in class org.apache.commons.math.ConvergingAlgorithmImpl
-
Deprecated.
Set the relative accuracy.
- setRelativeAccuracy(double) - Method in class org.apache.commons.math.optimization.MultiStartUnivariateRealOptimizer
-
Set the relative accuracy.
- setResult(double, int) - Method in class org.apache.commons.math.analysis.integration.UnivariateRealIntegratorImpl
-
Convenience function for implementations.
- setResult(double, int) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Convenience function for implementations.
- setResult(double, double, int) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Convenience function for implementations.
- setResult(double, double, int) - Method in class org.apache.commons.math.optimization.univariate.AbstractUnivariateRealOptimizer
-
Deprecated.
in 2.2 (no alternative).
- setRoundingMode(DfpField.RoundingMode) - Method in class org.apache.commons.math.dfp.DfpField
-
Set the rounding mode.
- setRoundingMode(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Sets the rounding mode for decimal divisions.
- setRoundingMode(RoundingMode) - Method in class org.apache.commons.math.util.BigReal
-
Sets the rounding mode for decimal divisions.
- setRow(int, T[]) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, T[]) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, double[]) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, T[]) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRow(int, double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowMatrix(int, RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in row number row
as a row matrix.
- setRowVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, RealVector) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Sets the entries in row number row
as a vector.
- setRowVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Sets the entries in row number row
as a vector.
- setSafety(double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Set the safety factor for stepsize control.
- setSafety(double) - Method in class org.apache.commons.math.ode.nonstiff.EmbeddedRungeKuttaIntegrator
-
Set the safety factor for stepsize control.
- setSampleSize(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
-
- setSampleSize(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setScale(double) - Method in interface org.apache.commons.math.distribution.CauchyDistribution
-
- setScale(double) - Method in class org.apache.commons.math.distribution.CauchyDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setScale(double) - Method in interface org.apache.commons.math.distribution.WeibullDistribution
-
- setScale(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setScale(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Sets the scale for division operations.
- setScale(int) - Method in class org.apache.commons.math.util.BigReal
-
Sets the scale for division operations.
- setSecureAlgorithm(String, String) - Method in class org.apache.commons.math.random.RandomDataImpl
-
Sets the PRNG algorithm for the underlying SecureRandom instance using
the Security Provider API.
- setSeed(int) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Sets the seed of the underlying random number generator using an
int
seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Sets the seed of the underlying random number generator using an
int
array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.AbstractRandomGenerator
-
Sets the seed of the underyling random number generator using a
long
seed.
- setSeed(int) - Method in class org.apache.commons.math.random.AbstractWell
-
Reinitialize the generator as if just built with the given int seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.AbstractWell
-
Reinitialize the generator as if just built with the given int array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.AbstractWell
-
Reinitialize the generator as if just built with the given long seed.
- setSeed(int) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Sets the seed of the underlying random number generator using an
int
seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Sets the seed of the underlying random number generator using an
int
array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.BitsStreamGenerator
-
Sets the seed of the underlying random number generator using a
long
seed.
- setSeed(int) - Method in class org.apache.commons.math.random.JDKRandomGenerator
-
Sets the seed of the underlying random number generator using an
int
seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.JDKRandomGenerator
-
Sets the seed of the underlying random number generator using an
int
array seed.
- setSeed(int) - Method in class org.apache.commons.math.random.MersenneTwister
-
Reinitialize the generator as if just built with the given int seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.MersenneTwister
-
Reinitialize the generator as if just built with the given int array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.MersenneTwister
-
Reinitialize the generator as if just built with the given long seed.
- setSeed(int) - Method in class org.apache.commons.math.random.RandomAdaptor
-
Sets the seed of the underlying random number generator using an
int
seed.
- setSeed(int[]) - Method in class org.apache.commons.math.random.RandomAdaptor
-
Sets the seed of the underlying random number generator using an
int
array seed.
- setSeed(long) - Method in class org.apache.commons.math.random.RandomAdaptor
-
Sets the seed of the underlying random number generator using a
long
seed.
- setSeed(int) - Method in interface org.apache.commons.math.random.RandomGenerator
-
Sets the seed of the underlying random number generator using an
int
seed.
- setSeed(int[]) - Method in interface org.apache.commons.math.random.RandomGenerator
-
Sets the seed of the underlying random number generator using an
int
array seed.
- setSeed(long) - Method in interface org.apache.commons.math.random.RandomGenerator
-
Sets the seed of the underlying random number generator using a
long
seed.
- setShape(double) - Method in interface org.apache.commons.math.distribution.WeibullDistribution
-
- setShape(double) - Method in class org.apache.commons.math.distribution.WeibullDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setSigma(double) - Method in class org.apache.commons.math.random.ValueServer
-
Setter for property sigma.
- setSkewnessImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the skewness.
- setSoftCurrentTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Restrict step range to a limited part of the global step.
- setSoftPreviousTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Restrict step range to a limited part of the global step.
- setStabilityCheck(boolean, int, int, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Set the stability check controls.
- setStandardDeviation(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
-
- setStandardDeviation(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
-
Deprecated.
as of 2.1 (class will become immutable in 3.0)
- setStartConfiguration(double[]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set start configuration for simplex.
- setStartConfiguration(double[][]) - Method in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Set start configuration for simplex.
- setStarterIntegrator(FirstOrderIntegrator) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Set the starter integrator.
- setStateInitialized(boolean) - Method in class org.apache.commons.math.ode.AbstractIntegrator
-
Set the stateInitialized flag.
- setSteadyStateThreshold(double) - Method in class org.apache.commons.math.estimation.GaussNewtonEstimator
-
Deprecated.
Set the steady state detection threshold.
- setStepsizeControl(double, double, double, double) - Method in class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
-
Set the step size control factors.
- setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(BigDecimal[][], int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(T[][], int, int) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(double[][], int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Replace the submatrix starting at row, column
using data in
the input subMatrix
array.
- setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Set a set of consecutive elements.
- setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Set a set of consecutive elements.
- setSubVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set a set of consecutive elements.
- setSubVector(int, T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Set a set of consecutive elements.
- setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set a set of consecutive elements.
- setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Set a set of consecutive elements.
- setSubVector(int, FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Set a set of consecutive elements.
- setSubVector(int, T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Set a set of consecutive elements.
- setSubVector(int, RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Set a set of consecutive elements.
- setSubVector(int, double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Set a set of consecutive elements.
- setSubVector(int, RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Set a set of consecutive elements.
- setSubVector(int, double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Set a set of consecutive elements.
- setSubVector(int, FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Set a set of consecutive elements.
- setSubVector(int, T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Set a set of consecutive elements.
- setSumImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the sum.
- setSumImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the Sum.
- setSumImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the Sum.
- setSumImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the Sum.
- setSumImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the Sum.
- setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
-
Sets the implementation for the sum of logs.
- setSumLogImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the sum of logs.
- setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the sum of logs.
- setSumLogImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the sum of logs.
- setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the sum of logs.
- setSumsqImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the sum of squares.
- setSumsqImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics
-
Sets the implementation for the sum of squares.
- setSumsqImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the sum of squares.
- setSumsqImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Sets the implementation for the sum of squares.
- setSumsqImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the sum of squares.
- setUnknownDistributionChiSquareTest(UnknownDistributionChiSquareTest) - Static method in class org.apache.commons.math.stat.inference.TestUtils
-
Deprecated.
2.2 will be removed in 3.0 - not compatible with use from multiple threads
- setValue(double) - Method in class org.apache.commons.math.linear.AbstractRealVector.EntryImpl
-
Set the value of the entry.
- setValue(double) - Method in class org.apache.commons.math.linear.OpenMapRealVector.OpenMapEntry
-
Set the value of the entry.
- setValue(double) - Method in class org.apache.commons.math.linear.RealVector.Entry
-
Set the value of the entry.
- setValuesFileURL(String) - Method in class org.apache.commons.math.random.ValueServer
-
Sets the valuesFileURL
using a string URL representation
- setValuesFileURL(URL) - Method in class org.apache.commons.math.random.ValueServer
-
Sets the valuesFileURL
- setVarianceDirection(SemiVariance.Direction) - Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
-
Sets the variance direction
- setVarianceImpl(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
Sets the implementation for the variance.
- setVarianceImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Sets the implementation for the variance.
- setVarianceImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Sets the implementation for the variance.
- setWholeFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
-
Modify the whole format.
- setWholeFormat(NumberFormat) - Method in class org.apache.commons.math.fraction.ProperFractionFormat
-
Modify the whole format.
- setWindowSize(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
-
WindowSize controls the number of values which contribute
to the reported statistics.
- setWindowSize(int) - Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
WindowSize controls the number of values which contribute
to the reported statistics.
- shift() - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Shift one step forward.
- shiftLeft() - Method in class org.apache.commons.math.dfp.Dfp
-
Shift the mantissa left, and adjust the exponent to compensate.
- shiftRight() - Method in class org.apache.commons.math.dfp.Dfp
-
Shift the mantissa right, and adjust the exponent to compensate.
- sign - Variable in class org.apache.commons.math.dfp.Dfp
-
Sign bit: & for positive, -1 for negative.
- sign(byte) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for byte value
x
.
- sign(double) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for double precision
x
.
- sign(float) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for float value
x
.
- sign(int) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for int value
x
.
- sign(long) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for long value
x
.
- sign(short) - Static method in class org.apache.commons.math.util.MathUtils
-
Returns the
sign
for short value
x
.
- SIGNUM - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- signum(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the signum of a number.
- signum(float) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the signum of a number.
- SimpleEstimationProblem - Class in org.apache.commons.math.estimation
-
Deprecated.
as of 2.0, everything in package org.apache.commons.math.estimation has
been deprecated and replaced by package org.apache.commons.math.optimization.general
- SimpleEstimationProblem() - Constructor for class org.apache.commons.math.estimation.SimpleEstimationProblem
-
Deprecated.
Build an empty instance without parameters nor measurements.
- SimpleRealPointChecker - Class in org.apache.commons.math.optimization
-
- SimpleRealPointChecker() - Constructor for class org.apache.commons.math.optimization.SimpleRealPointChecker
-
Build an instance with default threshold.
- SimpleRealPointChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleRealPointChecker
-
Build an instance with a specified threshold.
- SimpleRegression - Class in org.apache.commons.math.stat.regression
-
Estimates an ordinary least squares regression model
with one independent variable.
- SimpleRegression() - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
-
Create an empty SimpleRegression instance
- SimpleRegression(TDistribution) - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
-
- SimpleRegression(int) - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
-
Create an empty SimpleRegression.
- SimpleScalarValueChecker - Class in org.apache.commons.math.optimization
-
- SimpleScalarValueChecker() - Constructor for class org.apache.commons.math.optimization.SimpleScalarValueChecker
-
Build an instance with default threshold.
- SimpleScalarValueChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleScalarValueChecker
-
Build an instance with a specified threshold.
- SimpleVectorialPointChecker - Class in org.apache.commons.math.optimization
-
- SimpleVectorialPointChecker() - Constructor for class org.apache.commons.math.optimization.SimpleVectorialPointChecker
-
Build an instance with default threshold.
- SimpleVectorialPointChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleVectorialPointChecker
-
Build an instance with a specified threshold.
- SimpleVectorialValueChecker - Class in org.apache.commons.math.optimization
-
- SimpleVectorialValueChecker() - Constructor for class org.apache.commons.math.optimization.SimpleVectorialValueChecker
-
Build an instance with default threshold.
- SimpleVectorialValueChecker(double, double) - Constructor for class org.apache.commons.math.optimization.SimpleVectorialValueChecker
-
Build an instance with a specified threshold.
- simplex - Variable in class org.apache.commons.math.optimization.direct.DirectSearchOptimizer
-
Simplex.
- SimplexSolver - Class in org.apache.commons.math.optimization.linear
-
Solves a linear problem using the Two-Phase Simplex Method.
- SimplexSolver() - Constructor for class org.apache.commons.math.optimization.linear.SimplexSolver
-
Build a simplex solver with default settings.
- SimplexSolver(double) - Constructor for class org.apache.commons.math.optimization.linear.SimplexSolver
-
Build a simplex solver with a specified accepted amount of error
- SimpsonIntegrator - Class in org.apache.commons.math.analysis.integration
-
Implements the
Simpson's Rule for integration of real univariate functions.
- SimpsonIntegrator(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.integration.SimpsonIntegrator
-
- SimpsonIntegrator() - Constructor for class org.apache.commons.math.analysis.integration.SimpsonIntegrator
-
Construct an integrator.
- SIN - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- sin() - Method in class org.apache.commons.math.complex.Complex
-
Compute the
sine
of this complex number.
- sin(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
computes the sine of the argument.
- sin(double) - Static method in class org.apache.commons.math.util.FastMath
-
Sine function.
- SingularMatrixException - Exception in org.apache.commons.math.linear
-
Thrown when a matrix is singular.
- SingularMatrixException() - Constructor for exception org.apache.commons.math.linear.SingularMatrixException
-
Construct an exception with a default message.
- SingularValueDecomposition - Interface in org.apache.commons.math.linear
-
An interface to classes that implement an algorithm to calculate the
Singular Value Decomposition of a real matrix.
- SingularValueDecompositionImpl - Class in org.apache.commons.math.linear
-
Calculates the compact Singular Value Decomposition of a matrix.
- SingularValueDecompositionImpl(RealMatrix) - Constructor for class org.apache.commons.math.linear.SingularValueDecompositionImpl
-
Calculates the compact Singular Value Decomposition of the given matrix.
- SINH - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- sinh() - Method in class org.apache.commons.math.complex.Complex
-
- sinh(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the hyperbolic sine of a number.
- sinh(double) - Static method in class org.apache.commons.math.util.MathUtils
-
- sinInternal(Dfp[]) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Computes sin(a) Used when 0 < a < pi/4.
- size() - Method in class org.apache.commons.math.util.OpenIntToDoubleHashMap
-
Get the number of elements stored in the map.
- size() - Method in class org.apache.commons.math.util.OpenIntToFieldHashMap
-
Get the number of elements stored in the map.
- Skewness - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes the skewness of the available values.
- Skewness() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Constructs a Skewness
- Skewness(ThirdMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Constructs a Skewness with an external moment
- Skewness(Skewness) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
-
Copy constructor, creates a new Skewness
identical
to the original
- smooth(double[], double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
Compute a weighted loess fit on the data at the original abscissae.
- smooth(double[], double[]) - Method in class org.apache.commons.math.analysis.interpolation.LoessInterpolator
-
Compute a loess fit on the data at the original abscissae.
- SmoothingBicubicSplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
-
- SmoothingBicubicSplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingBicubicSplineInterpolator
-
Deprecated.
- SmoothingPolynomialBicubicSplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
-
Generates a bicubic interpolation function.
- SmoothingPolynomialBicubicSplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
Default constructor.
- SmoothingPolynomialBicubicSplineInterpolator(int) - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
- SmoothingPolynomialBicubicSplineInterpolator(int, int) - Constructor for class org.apache.commons.math.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
- SNAN - Static variable in class org.apache.commons.math.dfp.Dfp
-
Indicator value for signaling NaN.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Deprecated.
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Deprecated.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Solve for a zero in the given interval, start at startValue.
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Solve for a zero root in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BisectionSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Deprecated.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Find a zero in the given interval with an initial guess.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.BrentSolver
-
Find a zero in the given interval.
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Find a real root in the given interval with initial value.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Find a real root in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(Complex[], Complex) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Find a real root in the given interval with initial value.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Find a real root in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Find a zero near the midpoint of min
and max
.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Find a zero near the value startValue
.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.NewtonSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Find a root in the given interval with initial value.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Find a root in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.RiddersSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
- solve(double, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Find a zero in the given interval.
- solve(UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Find a zero in the given interval.
- solve(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.SecantSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
- solve(UnivariateRealFunction, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(double, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
- solve(UnivariateRealFunction, double, double, double) - Method in interface org.apache.commons.math.analysis.solvers.UnivariateRealSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solve(int, UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Solve for a zero root in the given interval.
- solve(int, UnivariateRealFunction, double, double, double) - Method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverImpl
-
Deprecated.
Solve for a zero in the given interval, start at startValue.
- solve(UnivariateRealFunction, double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
-
Convenience method to find a zero of a univariate real function.
- solve(UnivariateRealFunction, double, double, double) - Static method in class org.apache.commons.math.analysis.solvers.UnivariateRealSolverUtils
-
Convenience method to find a zero of a univariate real function.
- solve(double[]) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Deprecated.
- solve(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Deprecated.
- solve(BigDecimal[]) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns the solution vector for a linear system with coefficient
matrix = this and constant vector = b
.
- solve(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Returns a matrix of (column) solution vectors for linear systems with
coefficient matrix = this and constant vectors = columns of
b
.
- solve(BigDecimal[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a matrix of (column) solution vectors for linear systems with
coefficient matrix = this and constant vectors = columns of
b
.
- solve(double[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a matrix of (column) solution vectors for linear systems with
coefficient matrix = this and constant vectors = columns of
b
.
- solve(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Returns a matrix of (column) solution vectors for linear systems with
coefficient matrix = this and constant vectors = columns of
b
.
- solve(double[]) - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(RealVector) - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(RealMatrix) - Method in interface org.apache.commons.math.linear.DecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(T[]) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldDecompositionSolver
-
Solve the linear equation A × X = B for matrices A.
- solve(double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
-
- solve(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
- solve2(double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
- solve2(UnivariateRealFunction, double, double) - Method in class org.apache.commons.math.analysis.solvers.MullerSolver
-
Deprecated.
in 2.2 (to be removed in 3.0).
- solveAll(double[], double) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
- solveAll(Complex[], Complex) - Method in class org.apache.commons.math.analysis.solvers.LaguerreSolver
-
- solvePhase1(SimplexTableau) - Method in class org.apache.commons.math.optimization.linear.SimplexSolver
-
Solves Phase 1 of the Simplex method.
- SparseFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
Sparse matrix implementation based on an open addressed map.
- SparseFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
-
Creates a matrix with no data.
- SparseFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
-
Create a new SparseFieldMatrix with the supplied row and column dimensions.
- SparseFieldMatrix(SparseFieldMatrix<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
-
Copy constructor.
- SparseFieldMatrix(FieldMatrix<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldMatrix
-
Generic copy constructor.
- SparseFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math.linear
-
- SparseFieldVector(Field<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Build a 0-length vector.
- SparseFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Construct a (dimension)-length vector of zeros.
- SparseFieldVector(SparseFieldVector<T>, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Build a resized vector, for use with append.
- SparseFieldVector(Field<T>, int, int) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Build a vector with known the sparseness (for advanced use only).
- SparseFieldVector(Field<T>, T[]) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Create from a Field array.
- SparseFieldVector(SparseFieldVector<T>) - Constructor for class org.apache.commons.math.linear.SparseFieldVector
-
Copy constructor.
- sparseIterator() - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Specialized implementations may choose to not iterate over all
dimensions, either because those values are unset, or are equal
to defaultValue(), or are small enough to be ignored for the
purposes of iteration.
- sparseIterator() - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Specialized implementations may choose to not iterate over all
dimensions, either because those values are unset, or are equal
to defaultValue(), or are small enough to be ignored for the
purposes of iteration.
- sparseIterator() - Method in interface org.apache.commons.math.linear.RealVector
-
Specialized implementations may choose to not iterate over all
dimensions, either because those values are unset, or are equal
to defaultValue(), or are small enough to be ignored for the
purposes of iteration.
- SparseRealMatrix - Interface in org.apache.commons.math.linear
-
Marker interface for
RealMatrix
implementations that require sparse backing storage
- SparseRealVector - Interface in org.apache.commons.math.linear
-
Marker interface for RealVectors that require sparse backing storage
- SpearmansCorrelation - Class in org.apache.commons.math.stat.correlation
-
Spearman's rank correlation.
- SpearmansCorrelation(RealMatrix, RankingAlgorithm) - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Create a SpearmansCorrelation with the given input data matrix
and ranking algorithm.
- SpearmansCorrelation(RealMatrix) - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Create a SpearmansCorrelation from the given data matrix.
- SpearmansCorrelation() - Constructor for class org.apache.commons.math.stat.correlation.SpearmansCorrelation
-
Create a SpearmansCorrelation without data.
- SplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
-
Computes a natural (also known as "free", "unclamped") cubic spline interpolation for the data set.
- SplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.SplineInterpolator
-
- split(DfpField, String) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Breaks a string representation up into two dfp's.
- split(Dfp) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Splits a
Dfp
into 2
Dfp
's such that their sum is equal to the input
Dfp
.
- splitDiv(Dfp[], Dfp[]) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Divide two numbers that are split in to two pieces that are meant to be added together.
- splitMult(Dfp[], Dfp[]) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Multiply two numbers that are split in to two pieces that are
meant to be added together.
- splitPow(Dfp[], int) - Static method in class org.apache.commons.math.dfp.DfpMath
-
Raise a split base to the a power.
- SQRT - Static variable in class org.apache.commons.math.analysis.ComposableFunction
-
- sqrt() - Method in class org.apache.commons.math.complex.Complex
-
- sqrt() - Method in class org.apache.commons.math.dfp.Dfp
-
Compute the square root.
- sqrt(double) - Static method in class org.apache.commons.math.util.FastMath
-
Compute the square root of a number.
- sqrt1z() - Method in class org.apache.commons.math.complex.Complex
-
Compute the
square root of 1 -
this
2 for this complex
number.
- StandardDeviation - Class in org.apache.commons.math.stat.descriptive.moment
-
Computes the sample standard deviation.
- StandardDeviation() - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Constructs a StandardDeviation.
- StandardDeviation(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Constructs a StandardDeviation from an external second moment.
- StandardDeviation(StandardDeviation) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Copy constructor, creates a new StandardDeviation
identical
to the original
- StandardDeviation(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Contructs a StandardDeviation with the specified value for the
isBiasCorrected
property.
- StandardDeviation(boolean, SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
-
Contructs a StandardDeviation with the specified value for the
isBiasCorrected
property and the supplied external moment.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultFieldMatrixChangingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultFieldMatrixPreservingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultRealMatrixChangingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in class org.apache.commons.math.linear.DefaultRealMatrixPreservingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrixChangingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.FieldMatrixPreservingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrixChangingVisitor
-
Start visiting a matrix.
- start(int, int, int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrixPreservingVisitor
-
Start visiting a matrix.
- start(double, double[], double) - Method in class org.apache.commons.math.ode.MultistepIntegrator
-
Start the integration.
- start() - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Returns the starting index of the internal array.
- startIndex - Variable in class org.apache.commons.math.util.ResizableDoubleArray
-
The position of the first addressable element in the internal storage
array.
- stateVariation - Variable in class org.apache.commons.math.ode.sampling.NordsieckStepInterpolator
-
State variation.
- StatisticalMultivariateSummary - Interface in org.apache.commons.math.stat.descriptive
-
Reporting interface for basic multivariate statistics.
- StatisticalSummary - Interface in org.apache.commons.math.stat.descriptive
-
Reporting interface for basic univariate statistics.
- StatisticalSummaryValues - Class in org.apache.commons.math.stat.descriptive
-
Value object representing the results of a univariate statistical summary.
- StatisticalSummaryValues(double, double, long, double, double, double) - Constructor for class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
Constructor
- StatUtils - Class in org.apache.commons.math.stat
-
StatUtils provides static methods for computing statistics based on data
stored in double[] arrays.
- stepAccepted(double, double[]) - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Inform the event handlers that the step has been accepted
by the integrator.
- stepAccepted(double, double[]) - Method in class org.apache.commons.math.ode.events.EventState
-
Acknowledge the fact the step has been accepted by the integrator.
- StepHandler - Interface in org.apache.commons.math.ode.sampling
-
This interface represents a handler that should be called after
each successful step.
- stepHandlers - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Step handler.
- StepHandlerWithJacobians - Interface in org.apache.commons.math.ode.jacobians
-
Deprecated.
as of 2.2 the complete package is deprecated, it will be replaced
in 3.0 by a completely rewritten implementation
- StepInterpolator - Interface in org.apache.commons.math.ode.sampling
-
This interface represents an interpolator over the last step
during an ODE integration.
- StepInterpolatorWithJacobians - Interface in org.apache.commons.math.ode.jacobians
-
Deprecated.
as of 2.2 the complete package is deprecated, it will be replaced
in 3.0 by a completely rewritten implementation
- StepNormalizer - Class in org.apache.commons.math.ode.sampling
-
- StepNormalizer(double, FixedStepHandler) - Constructor for class org.apache.commons.math.ode.sampling.StepNormalizer
-
Simple constructor.
- stepSize - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Current stepsize.
- stepStart - Variable in class org.apache.commons.math.ode.AbstractIntegrator
-
Current step start time.
- stop() - Method in class org.apache.commons.math.ode.events.CombinedEventsManager
-
Deprecated.
Check if the integration should be stopped at the end of the
current step.
- STOP - Static variable in interface org.apache.commons.math.ode.events.EventHandler
-
Stop indicator.
- stop() - Method in class org.apache.commons.math.ode.events.EventState
-
Check if the integration should be stopped at the end of the
current step.
- STOP - Static variable in interface org.apache.commons.math.ode.jacobians.EventHandlerWithJacobians
-
Deprecated.
Stop indicator.
- StoppingCondition - Interface in org.apache.commons.math.genetics
-
Algorithm used to determine when to stop evolution.
- StorelessUnivariateStatistic - Interface in org.apache.commons.math.stat.descriptive
-
- storeTime(double) - Method in class org.apache.commons.math.ode.sampling.AbstractStepInterpolator
-
Store the current step time.
- subAndCheck(int, int) - Static method in class org.apache.commons.math.util.MathUtils
-
Subtract two integers, checking for overflow.
- subAndCheck(long, long) - Static method in class org.apache.commons.math.util.MathUtils
-
Subtract two long integers, checking for overflow.
- substituteMostRecentElement(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
-
Substitutes value
for the most recently added value.
- SUBTRACT - Static variable in class org.apache.commons.math.analysis.BinaryFunction
-
Deprecated.
- subtract(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.ComposableFunction
-
Return a function subtracting another function from the instance.
- subtract(PolynomialFunction) - Method in class org.apache.commons.math.analysis.polynomials.PolynomialFunction
-
Subtract a polynomial from the instance.
- subtract(Complex) - Method in class org.apache.commons.math.complex.Complex
-
Return the difference between this complex number and the given complex
number.
- subtract(Dfp) - Method in class org.apache.commons.math.dfp.Dfp
-
Subtract x from this.
- subtract(T) - Method in interface org.apache.commons.math.FieldElement
-
Compute this - a.
- subtract(BigInteger) - Method in class org.apache.commons.math.fraction.BigFraction
-
Subtracts the value of an
BigInteger
from the value of this one,
returning the result in reduced form.
- subtract(int) - Method in class org.apache.commons.math.fraction.BigFraction
-
Subtracts the value of an integer from the value of this one,
returning the result in reduced form.
- subtract(long) - Method in class org.apache.commons.math.fraction.BigFraction
-
Subtracts the value of an integer from the value of this one,
returning the result in reduced form.
- subtract(BigFraction) - Method in class org.apache.commons.math.fraction.BigFraction
-
Subtracts the value of another fraction from the value of this one,
returning the result in reduced form.
- subtract(Fraction) - Method in class org.apache.commons.math.fraction.Fraction
-
Subtracts the value of another fraction from the value of this one,
returning the result in reduced form.
- subtract(int) - Method in class org.apache.commons.math.fraction.Fraction
-
Subtract an integer from the fraction.
- subtract(Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
-
Subtract a vector from the instance.
- subtract(double, Vector3D) - Method in class org.apache.commons.math.geometry.Vector3D
-
Subtract a scaled vector from the instance.
- subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.AbstractFieldMatrix
-
Compute this minus m.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.AbstractRealMatrix
-
Compute this minus m.
- subtract(double[]) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Subtract v
from this vector.
- subtract(RealVector) - Method in class org.apache.commons.math.linear.AbstractRealVector
-
Subtract v
from this vector.
- subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Compute this minus m.
- subtract(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math.linear.Array2DRowFieldMatrix
-
Compute this minus m
.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Compute this minus m.
- subtract(Array2DRowRealMatrix) - Method in class org.apache.commons.math.linear.Array2DRowRealMatrix
-
Compute this minus m
.
- subtract(FieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute this minus v.
- subtract(T[]) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute this minus v.
- subtract(ArrayFieldVector<T>) - Method in class org.apache.commons.math.linear.ArrayFieldVector
-
Compute this minus v.
- subtract(RealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Subtract v
from this vector.
- subtract(double[]) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Subtract v
from this vector.
- subtract(ArrayRealVector) - Method in class org.apache.commons.math.linear.ArrayRealVector
-
Compute this minus v.
- subtract(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
-
Deprecated.
Compute this minus m.
- subtract(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Compute this minus m
.
- subtract(BigMatrixImpl) - Method in class org.apache.commons.math.linear.BigMatrixImpl
-
Deprecated.
Compute this minus m
.
- subtract(FieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Compute this minus m.
- subtract(BlockFieldMatrix<T>) - Method in class org.apache.commons.math.linear.BlockFieldMatrix
-
Compute this minus m
.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Compute this minus m.
- subtract(BlockRealMatrix) - Method in class org.apache.commons.math.linear.BlockRealMatrix
-
Compute this minus m
.
- subtract(FieldMatrix<T>) - Method in interface org.apache.commons.math.linear.FieldMatrix
-
Compute this minus m.
- subtract(FieldVector<T>) - Method in interface org.apache.commons.math.linear.FieldVector
-
Compute this minus v.
- subtract(T[]) - Method in interface org.apache.commons.math.linear.FieldVector
-
Compute this minus v.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute this minus m.
- subtract(OpenMapRealMatrix) - Method in class org.apache.commons.math.linear.OpenMapRealMatrix
-
Compute this minus m
.
- subtract(OpenMapRealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Optimized method to subtract OpenMapRealVectors.
- subtract(RealVector) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Subtract v
from this vector.
- subtract(double[]) - Method in class org.apache.commons.math.linear.OpenMapRealVector
-
Subtract v
from this vector.
- subtract(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
-
Compute this minus m.
- subtract(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Compute this minus m.
- subtract(RealMatrixImpl) - Method in class org.apache.commons.math.linear.RealMatrixImpl
-
Deprecated.
Compute this minus m
.
- subtract(RealVector) - Method in interface org.apache.commons.math.linear.RealVector
-
Subtract v
from this vector.
- subtract(double[]) - Method in interface org.apache.commons.math.linear.RealVector
-
Subtract v
from this vector.
- subtract(SparseFieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Optimized method to subtract SparseRealVectors.
- subtract(FieldVector<T>) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Compute this minus v.
- subtract(T[]) - Method in class org.apache.commons.math.linear.SparseFieldVector
-
Compute this minus v.
- subtract(BigReal) - Method in class org.apache.commons.math.util.BigReal
-
Compute this - a.
- Sum - Class in org.apache.commons.math.stat.descriptive.summary
-
Returns the sum of the available values.
- Sum() - Constructor for class org.apache.commons.math.stat.descriptive.summary.Sum
-
Create a Sum instance
- Sum(Sum) - Constructor for class org.apache.commons.math.stat.descriptive.summary.Sum
-
Copy constructor, creates a new Sum
identical
to the original
- sum - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
sum of values that have been added
- sum(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the values in the input array, or
Double.NaN
if the array is empty.
- sum(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the entries in the specified portion of
the input array, or Double.NaN
if the designated subarray
is empty.
- sumDifference(double[], double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the (signed) differences between corresponding elements of the
input arrays -- i.e., sum(sample1[i] - sample2[i]).
- sumLog - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
sumLog of values that have been added
- sumLog(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the natural logs of the entries in the input array, or
Double.NaN
if the array is empty.
- sumLog(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the natural logs of the entries in the specified portion of
the input array, or Double.NaN
if the designated subarray
is empty.
- SummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
Computes summary statistics for a stream of data values added using the
addValue
method.
- SummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
Construct a SummaryStatistics instance
- SummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
A copy constructor.
- SumOfLogs - Class in org.apache.commons.math.stat.descriptive.summary
-
Returns the sum of the natural logs for this collection of values.
- SumOfLogs() - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Create a SumOfLogs instance
- SumOfLogs(SumOfLogs) - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
-
Copy constructor, creates a new SumOfLogs
identical
to the original
- SumOfSquares - Class in org.apache.commons.math.stat.descriptive.summary
-
Returns the sum of the squares of the available values.
- SumOfSquares() - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Create a SumOfSquares instance
- SumOfSquares(SumOfSquares) - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
-
Copy constructor, creates a new SumOfSquares
identical
to the original
- sumsq - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
-
sum of the square of each value that has been added
- sumSq(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the squares of the entries in the input array, or
Double.NaN
if the array is empty.
- sumSq(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
-
Returns the sum of the squares of the entries in the specified portion of
the input array, or Double.NaN
if the designated subarray
is empty.
- SynchronizedDescriptiveStatistics - Class in org.apache.commons.math.stat.descriptive
-
- SynchronizedDescriptiveStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Construct an instance with infinite window
- SynchronizedDescriptiveStatistics(int) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
Construct an instance with finite window
- SynchronizedDescriptiveStatistics(SynchronizedDescriptiveStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
-
A copy constructor.
- SynchronizedMultivariateSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
- SynchronizedMultivariateSummaryStatistics(int, boolean) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics
-
Construct a SynchronizedMultivariateSummaryStatistics instance
- SynchronizedSummaryStatistics - Class in org.apache.commons.math.stat.descriptive
-
Implementation of
SummaryStatistics
that
is safe to use in a multithreaded environment.
- SynchronizedSummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
Construct a SynchronizedSummaryStatistics instance
- SynchronizedSummaryStatistics(SynchronizedSummaryStatistics) - Constructor for class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
-
A copy constructor.