Index (Apache Commons RNG Sampling 1.5 API)

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

A

add(S, double) - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.Builder: Adds the sampler to the composite.
AhrensDieterExponentialSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from an exponential distribution.
AhrensDieterExponentialSampler(UniformRandomProvider, double) - Constructor for class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler
AhrensDieterMarsagliaTsangGammaSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from the gamma distribution.
AhrensDieterMarsagliaTsangGammaSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler: This instance delegates sampling.
alias - Variable in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler: The alias table.
ALIAS_METHOD - org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler: Sample using the alias method (see AliasMethodDiscreteSampler).
AliasMethodDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution: Distribution sampler that uses the Alias method.

B

BoxMullerGaussianSampler - Class in org.apache.commons.rng.sampling.distribution: Deprecated.
Since version 1.1. Please use BoxMullerNormalizedGaussianSampler and GaussianSampler instead.
BoxMullerGaussianSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.BoxMullerGaussianSampler: Deprecated.
BoxMullerLogNormalSampler - Class in org.apache.commons.rng.sampling.distribution: Deprecated.
Since version 1.1. Please use LogNormalSampler instead.
BoxMullerLogNormalSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.BoxMullerLogNormalSampler: Deprecated.
BoxMullerNormalizedGaussianSampler - Class in org.apache.commons.rng.sampling.distribution: Box-Muller algorithm for sampling from Gaussian distribution with mean 0 and standard deviation 1.
BoxMullerNormalizedGaussianSampler(UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler
BoxSampler - Class in org.apache.commons.rng.sampling.shape: Generate points uniformly distributed within a n-dimension box (hyperrectangle).
build(UniformRandomProvider) - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.Builder: Builds the composite sampler.

C

ChengBetaSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a beta distribution.
ChengBetaSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.ChengBetaSampler: Creates a sampler instance.
CollectionSampler<T> - Class in org.apache.commons.rng.sampling: Sampling from a Collection.
CollectionSampler(UniformRandomProvider, Collection<T>) - Constructor for class org.apache.commons.rng.sampling.CollectionSampler: Creates a sampler.
CombinationSampler - Class in org.apache.commons.rng.sampling: Class for representing combinations of a sequence of integers.
CombinationSampler(UniformRandomProvider, int, int) - Constructor for class org.apache.commons.rng.sampling.CombinationSampler: Creates a generator of combinations.
CompositeSamplers - Class in org.apache.commons.rng.sampling: Factory class to create a sampler that combines sampling from multiple samplers.
CompositeSamplers.Builder<S> - Interface in org.apache.commons.rng.sampling: Builds a composite sampler.
CompositeSamplers.DiscreteProbabilitySampler - Enum in org.apache.commons.rng.sampling: The DiscreteProbabilitySampler class defines implementations that sample from a user-defined discrete probability distribution.
CompositeSamplers.DiscreteProbabilitySamplerFactory - Interface in org.apache.commons.rng.sampling: A factory for creating a sampler of a user-defined discrete probability distribution.
ContinuousInverseCumulativeProbabilityFunction - Interface in org.apache.commons.rng.sampling.distribution: Interface for a continuous distribution that can be sampled using the inversion method.
ContinuousSampler - Interface in org.apache.commons.rng.sampling.distribution: Sampler that generates values of type double.
ContinuousUniformSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a uniform distribution.
ContinuousUniformSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler
create(UniformRandomProvider, double[]) - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySamplerFactory: Creates the sampler.
createPoissonSampler(UniformRandomProvider, double) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache: Deprecated.
Use PoissonSamplerCache.createSharedStateSampler(UniformRandomProvider, double).
createSample(double, double) - Method in class org.apache.commons.rng.sampling.shape.LineSampler: Creates the sample given the random variate u in the interval [0, 1].
createSample(double, double, double) - Method in class org.apache.commons.rng.sampling.shape.TriangleSampler: Creates the sample given the random variates s and t in the interval [0, 1] and s + t <= 1.
createSharedStateSampler(UniformRandomProvider, double) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache: Creates a new Poisson sampler.

D

DirichletSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a Dirichlet distribution.
DiscreteInverseCumulativeProbabilityFunction - Interface in org.apache.commons.rng.sampling.distribution: Interface for a discrete distribution that can be sampled using the inversion method.
DiscreteProbabilityCollectionSampler<T> - Class in org.apache.commons.rng.sampling: Sampling from a collection of items with user-defined probabilities.
DiscreteProbabilityCollectionSampler(UniformRandomProvider, List<T>, double[]) - Constructor for class org.apache.commons.rng.sampling.DiscreteProbabilityCollectionSampler: Creates a sampler.
DiscreteProbabilityCollectionSampler(UniformRandomProvider, Map<T, Double>) - Constructor for class org.apache.commons.rng.sampling.DiscreteProbabilityCollectionSampler: Creates a sampler.
DiscreteSampler - Interface in org.apache.commons.rng.sampling.distribution: Sampler that generates values of type int.
DiscreteUniformSampler - Class in org.apache.commons.rng.sampling.distribution: Discrete uniform distribution sampler.
DiscreteUniformSampler(UniformRandomProvider, int, int) - Constructor for class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler: This instance delegates sampling.

F

FastLoadedDiceRollerDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution: Distribution sampler that uses the Fast Loaded Dice Roller (FLDR).

G

GaussianSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a Gaussian distribution with given mean and standard deviation.
GaussianSampler(NormalizedGaussianSampler, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.GaussianSampler
GeometricSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a geometric distribution.
getK() - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler: Gets the number of categories.
getMaxMean() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache: Gets the maximum mean covered by the cache.
getMinimumCachedMean() - Static method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache: Gets the minimum mean value that can be cached.
getMinMean() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache: Gets the minimum mean covered by the cache.
GUIDE_TABLE - org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler: Sample using a guide table (see GuideTableDiscreteSampler).
GuideTableDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution: Compute a sample from n values each with an associated probability.

I

inverseCumulativeProbability(double) - Method in interface org.apache.commons.rng.sampling.distribution.ContinuousInverseCumulativeProbabilityFunction: Computes the quantile function of the distribution.
inverseCumulativeProbability(double) - Method in interface org.apache.commons.rng.sampling.distribution.DiscreteInverseCumulativeProbabilityFunction: Computes the quantile function of the distribution.
InverseTransformContinuousSampler - Class in org.apache.commons.rng.sampling.distribution: Distribution sampler that uses the inversion method.
InverseTransformContinuousSampler(UniformRandomProvider, ContinuousInverseCumulativeProbabilityFunction) - Constructor for class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler
InverseTransformDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution: Distribution sampler that uses the inversion method.
InverseTransformDiscreteSampler(UniformRandomProvider, DiscreteInverseCumulativeProbabilityFunction) - Constructor for class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler
InverseTransformParetoSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a Pareto distribution.
InverseTransformParetoSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler
isValidRange() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache: Checks if the cache covers a valid range of mean values.

K

KempSmallMeanPoissonSampler - Class in org.apache.commons.rng.sampling.distribution: Sampler for the Poisson distribution.

L

LargeMeanPoissonSampler - Class in org.apache.commons.rng.sampling.distribution: Sampler for the Poisson distribution.
LargeMeanPoissonSampler(UniformRandomProvider, double) - Constructor for class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler
LevySampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a Lévy distribution.
LineSampler - Class in org.apache.commons.rng.sampling.shape: Generate points uniformly distributed on a line.
ListSampler - Class in org.apache.commons.rng.sampling: Sampling from a List.
LogNormalSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a log-normal distribution.
LogNormalSampler(NormalizedGaussianSampler, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.LogNormalSampler
LongSampler - Interface in org.apache.commons.rng.sampling.distribution: Sampler that generates values of type long.
LOOKUP_TABLE - org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler: Sample using an optimised look-up table (see MarsagliaTsangWangDiscreteSampler.Enumerated).

M

MarsagliaNormalizedGaussianSampler - Class in org.apache.commons.rng.sampling.distribution: Marsaglia polar method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.
MarsagliaNormalizedGaussianSampler(UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler
MarsagliaTsangWangDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution: Sampler for a discrete distribution using an optimised look-up table.
MarsagliaTsangWangDiscreteSampler.Binomial - Class in org.apache.commons.rng.sampling.distribution: Create a sampler for the Binomial distribution.
MarsagliaTsangWangDiscreteSampler.Enumerated - Class in org.apache.commons.rng.sampling.distribution: Create a sampler for an enumerated distribution of n values each with an associated probability.
MarsagliaTsangWangDiscreteSampler.Poisson - Class in org.apache.commons.rng.sampling.distribution: Create a sampler for the Poisson distribution.

N

natural(int) - Static method in class org.apache.commons.rng.sampling.PermutationSampler: Creates an array representing the natural number n.
newContinuousSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers: Create a new builder for a composite ContinuousSampler.
newDiscreteSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers: Create a new builder for a composite DiscreteSampler.
newLongSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers: Create a new builder for a composite LongSampler.
newObjectSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers: Create a new builder for a composite ObjectSampler.
newSharedStateContinuousSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers: Create a new builder for a composite SharedStateContinuousSampler.
newSharedStateDiscreteSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers: Create a new builder for a composite SharedStateDiscreteSampler.
newSharedStateLongSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers: Create a new builder for a composite SharedStateLongSampler.
newSharedStateObjectSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers: Create a new builder for a composite SharedStateObjectSampler.
nextDouble() - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase: Deprecated.
nextGamma(int) - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler: Create a gamma sample for the given category.
nextInt() - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase: Deprecated.
nextInt(int) - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase: Deprecated.
nextLong() - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase: Deprecated.
nextVector() - Method in class org.apache.commons.rng.sampling.UnitSphereSampler: Deprecated.
Use UnitSphereSampler.sample().
NormalizedGaussianSampler - Interface in org.apache.commons.rng.sampling.distribution: Marker interface for a sampler that generates values from an N(0,1) Gaussian distribution.

O

ObjectSampler<T> - Interface in org.apache.commons.rng.sampling: Sampler that generates values of a specified type.
of(NormalizedGaussianSampler, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.GaussianSampler: Create a new normalised Gaussian sampler.
of(NormalizedGaussianSampler, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.LogNormalSampler: Create a new log-normal distribution sampler.
of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler: Create a new normalised Gaussian sampler.
of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler: Create a new normalised Gaussian sampler.
of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler: Create a new normalised Gaussian sampler.
of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential: Create a new exponential sampler with mean = 1.
of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.NormalizedGaussian: Create a new normalised Gaussian sampler.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler: Create a new exponential distribution sampler.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.GeometricSampler: Creates a new geometric distribution sampler.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler: Creates a new sampler for the Poisson distribution.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler: Creates a new Poisson distribution sampler.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.Poisson: Creates a sampler for the Poisson distribution.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.PoissonSampler: Creates a new Poisson distribution sampler.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler: Creates a new sampler for the Poisson distribution.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.TSampler: Create a new t distribution sampler.
of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential: Create a new exponential sampler with the specified mean.
of(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler: Creates a sampler.
of(UniformRandomProvider, double...) - Static method in class org.apache.commons.rng.sampling.distribution.DirichletSampler: Creates a new Dirichlet distribution sampler.
of(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.distribution.FastLoadedDiceRollerDiscreteSampler: Creates a sampler.
of(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler: Create a new sampler for an enumerated distribution using the given probabilities.
of(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.Enumerated: Creates a sampler for an enumerated distribution of n values each with an associated probability.
of(UniformRandomProvider, double[], double) - Static method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler: Create a new sampler for an enumerated distribution using the given probabilities.
of(UniformRandomProvider, double[], double[]) - Static method in class org.apache.commons.rng.sampling.shape.BoxSampler: Create a box sampler with bounds a and b.
of(UniformRandomProvider, double[], double[]) - Static method in class org.apache.commons.rng.sampling.shape.LineSampler: Create a line sampler with vertices a and b.
of(UniformRandomProvider, double[], double[], double[]) - Static method in class org.apache.commons.rng.sampling.shape.TriangleSampler: Create a triangle sampler with vertices a, b and c.
of(UniformRandomProvider, double[], double[], double[], double[]) - Static method in class org.apache.commons.rng.sampling.shape.TetrahedronSampler: Create a tetrahedron sampler with vertices a, b, c and d.
of(UniformRandomProvider, double[], int) - Static method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler: Creates a sampler.
of(UniformRandomProvider, double[], int) - Static method in class org.apache.commons.rng.sampling.distribution.FastLoadedDiceRollerDiscreteSampler: Creates a sampler.
of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler: Creates a new gamma distribution sampler.
of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.ChengBetaSampler: Creates a new beta distribution sampler.
of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler: Creates a new continuous uniform distribution sampler.
of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler: Creates a new Pareto distribution sampler.
of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.LevySampler: Create a new Lévy distribution sampler.
of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.StableSampler: Creates a standardized sampler of a stable distribution with zero location and unit scale.
of(UniformRandomProvider, double, double, boolean) - Static method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler: Creates a new continuous uniform distribution sampler.
of(UniformRandomProvider, double, double, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.StableSampler: Creates a sampler of a stable distribution.
of(UniformRandomProvider, int) - Static method in class org.apache.commons.rng.sampling.shape.UnitBallSampler: Create a unit n-ball sampler for the given dimension.
of(UniformRandomProvider, int) - Static method in class org.apache.commons.rng.sampling.UnitSphereSampler: Create a unit sphere sampler for the given dimension.
of(UniformRandomProvider, int, double) - Static method in class org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.Binomial: Creates a sampler for the Binomial distribution.
of(UniformRandomProvider, int, double) - Static method in class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler: Creates a new Zipf distribution sampler.
of(UniformRandomProvider, int, int) - Static method in class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler: Creates a new discrete uniform distribution sampler.
of(UniformRandomProvider, long[]) - Static method in class org.apache.commons.rng.sampling.distribution.FastLoadedDiceRollerDiscreteSampler: Creates a sampler.
of(UniformRandomProvider, long, long) - Static method in class org.apache.commons.rng.sampling.distribution.UniformLongSampler: Creates a new discrete uniform distribution sampler.
of(UniformRandomProvider, ContinuousInverseCumulativeProbabilityFunction) - Static method in class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler: Create a new inverse-transform continuous sampler.
of(UniformRandomProvider, DiscreteInverseCumulativeProbabilityFunction) - Static method in class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler: Create a new inverse-transform discrete sampler.
org.apache.commons.rng.sampling - package org.apache.commons.rng.sampling: This package provides sampling utilities.
org.apache.commons.rng.sampling.distribution - package org.apache.commons.rng.sampling.distribution: This package contains classes for sampling from statistical distributions.
org.apache.commons.rng.sampling.shape - package org.apache.commons.rng.sampling.shape: This package contains classes for sampling coordinates from shapes, for example a unit ball.

P

PermutationSampler - Class in org.apache.commons.rng.sampling: Class for representing permutations of a sequence of integers.
PermutationSampler(UniformRandomProvider, int, int) - Constructor for class org.apache.commons.rng.sampling.PermutationSampler: Creates a generator of permutations.
PoissonSampler - Class in org.apache.commons.rng.sampling.distribution: Sampler for the Poisson distribution.
PoissonSampler(UniformRandomProvider, double) - Constructor for class org.apache.commons.rng.sampling.distribution.PoissonSampler: This instance delegates sampling.
PoissonSamplerCache - Class in org.apache.commons.rng.sampling.distribution: Create a sampler for the Poisson distribution using a cache to minimise construction cost.
PoissonSamplerCache(double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
probability - Variable in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler: The probability table.

R

RejectionInversionZipfSampler - Class in org.apache.commons.rng.sampling.distribution: Implementation of the Zipf distribution.
RejectionInversionZipfSampler(UniformRandomProvider, int, double) - Constructor for class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler: This instance delegates sampling.
rng - Variable in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler: Underlying source of randomness.
rng - Variable in class org.apache.commons.rng.sampling.distribution.UniformLongSampler: Underlying source of randomness.

S

sample() - Method in class org.apache.commons.rng.sampling.CollectionSampler: Picks one of the items from the collection passed to the constructor.
sample() - Method in class org.apache.commons.rng.sampling.CombinationSampler: Return a combination of k whose entries are selected randomly, without repetition, from the integers 0, 1, ..., n-1 (inclusive).
sample() - Method in class org.apache.commons.rng.sampling.DiscreteProbabilityCollectionSampler: Picks one of the items from the collection passed to the constructor.
sample() - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerGaussianSampler: Deprecated.

Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerLogNormalSampler: Deprecated.

Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.ChengBetaSampler: Creates a double sample.
sample() - Method in interface org.apache.commons.rng.sampling.distribution.ContinuousSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
sample() - Method in interface org.apache.commons.rng.sampling.distribution.DiscreteSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.GaussianSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.LevySampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.LogNormalSampler: Creates a double sample.
sample() - Method in interface org.apache.commons.rng.sampling.distribution.LongSampler: Creates a long sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler: Rejection inversion sampling method for a discrete, bounded Zipf distribution that is based on the method described in Wolfgang Hörmann and Gerhard Derflinger.
sample() - Method in class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler: Creates an int sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.StableSampler: Generate a sample from a stable distribution.
sample() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential: Creates a double sample.
sample() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.NormalizedGaussian: Creates a double sample.
sample() - Method in interface org.apache.commons.rng.sampling.ObjectSampler: Create an object sample.
sample() - Method in class org.apache.commons.rng.sampling.PermutationSampler
sample() - Method in class org.apache.commons.rng.sampling.shape.BoxSampler
sample() - Method in class org.apache.commons.rng.sampling.shape.LineSampler
sample() - Method in class org.apache.commons.rng.sampling.shape.TetrahedronSampler
sample() - Method in class org.apache.commons.rng.sampling.shape.TriangleSampler
sample() - Method in class org.apache.commons.rng.sampling.shape.UnitBallSampler
sample() - Method in class org.apache.commons.rng.sampling.UnitSphereSampler
sample(UniformRandomProvider, List<T>, int) - Static method in class org.apache.commons.rng.sampling.ListSampler: Generates a list of size k whose entries are selected randomly, without repetition, from the items in the given collection.
SamplerBase - Class in org.apache.commons.rng.sampling.distribution: Deprecated.
Since version 1.1. Class intended for internal use only.
SamplerBase(UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.distribution.SamplerBase: Deprecated.
samples() - Method in interface org.apache.commons.rng.sampling.distribution.ContinuousSampler: Returns an effectively unlimited stream of double sample values.
samples() - Method in interface org.apache.commons.rng.sampling.distribution.DiscreteSampler: Returns an effectively unlimited stream of int sample values.
samples() - Method in interface org.apache.commons.rng.sampling.distribution.LongSampler: Returns an effectively unlimited stream of long sample values.
samples() - Method in interface org.apache.commons.rng.sampling.ObjectSampler: Returns an effectively unlimited stream of object sample values.
samples(long) - Method in interface org.apache.commons.rng.sampling.distribution.ContinuousSampler: Returns a stream producing the given streamSize number of double sample values.
samples(long) - Method in interface org.apache.commons.rng.sampling.distribution.DiscreteSampler: Returns a stream producing the given streamSize number of int sample values.
samples(long) - Method in interface org.apache.commons.rng.sampling.distribution.LongSampler: Returns a stream producing the given streamSize number of long sample values.
samples(long) - Method in interface org.apache.commons.rng.sampling.ObjectSampler: Returns a stream producing the given streamSize number of object sample values.
setFactory(CompositeSamplers.DiscreteProbabilitySamplerFactory) - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.Builder: Sets the factory to use to generate the composite's discrete sampler from the sampler weights.
SharedStateContinuousSampler - Interface in org.apache.commons.rng.sampling.distribution: Sampler that generates values of type double and can create new instances to sample from the same state with a given source of randomness.
SharedStateDiscreteSampler - Interface in org.apache.commons.rng.sampling.distribution: Sampler that generates values of type int and can create new instances to sample from the same state with a given source of randomness.
SharedStateLongSampler - Interface in org.apache.commons.rng.sampling.distribution: Sampler that generates values of type long and can create new instances to sample from the same state with a given source of randomness.
SharedStateObjectSampler<T> - Interface in org.apache.commons.rng.sampling: Sampler that generates values of a specified type and can create new instances to sample from the same state with a given source of randomness.
SharedStateSampler<R> - Interface in org.apache.commons.rng.sampling: Applies to samplers that can share state between instances.
shuffle(UniformRandomProvider, int[]) - Static method in class org.apache.commons.rng.sampling.PermutationSampler: Shuffles the entries of the given array.
shuffle(UniformRandomProvider, int[], int, boolean) - Static method in class org.apache.commons.rng.sampling.PermutationSampler: Shuffles the entries of the given array, using the Fisher-Yates algorithm.
shuffle(UniformRandomProvider, List<T>) - Static method in class org.apache.commons.rng.sampling.ListSampler: Shuffles the entries of the given array, using the Fisher-Yates algorithm.
shuffle(UniformRandomProvider, List<T>, int, boolean) - Static method in class org.apache.commons.rng.sampling.ListSampler: Shuffles the entries of the given array, using the Fisher-Yates algorithm.
size() - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.Builder: Return the number of samplers in the composite.
SmallMeanPoissonSampler - Class in org.apache.commons.rng.sampling.distribution: Sampler for the Poisson distribution.
SmallMeanPoissonSampler(UniformRandomProvider, double) - Constructor for class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler
StableSampler - Class in org.apache.commons.rng.sampling.distribution: Samples from a stable distribution.
symmetric(UniformRandomProvider, int, double) - Static method in class org.apache.commons.rng.sampling.distribution.DirichletSampler: Creates a new symmetric Dirichlet distribution sampler using the same concentration parameter for each category.

T

TetrahedronSampler - Class in org.apache.commons.rng.sampling.shape: Generate points uniformly distributed within a tetrahedron.
toString() - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerGaussianSampler: Deprecated.
toString() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerLogNormalSampler: Deprecated.
toString() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.ChengBetaSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.GaussianSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.LevySampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.LogNormalSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase: Deprecated.
toString() - Method in class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.StableSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.TSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.UniformLongSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
toString() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential
toString() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.NormalizedGaussian
TriangleSampler - Class in org.apache.commons.rng.sampling.shape: Generate points uniformly distributed within a triangle.
TSampler - Class in org.apache.commons.rng.sampling.distribution: Sampling from a T distribution.

U

UniformLongSampler - Class in org.apache.commons.rng.sampling.distribution: Discrete uniform distribution sampler generating values of type long.
UnitBallSampler - Class in org.apache.commons.rng.sampling.shape: Generate coordinates uniformly distributed within the unit n-ball.
UnitBallSampler() - Constructor for class org.apache.commons.rng.sampling.shape.UnitBallSampler
UnitSphereSampler - Class in org.apache.commons.rng.sampling: Generate vectors isotropically located on the surface of a sphere.
UnitSphereSampler(int, UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.UnitSphereSampler: Deprecated.
Use UnitSphereSampler.of(UniformRandomProvider, int).

V

valueOf(String) - Static method in enum org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler: Returns the enum constant of this type with the specified name.
values() - Static method in enum org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler: Returns an array containing the constants of this enum type, in the order they are declared.

W

withinRange(double) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache: Check if the mean is within the range where the cache can minimise the construction cost of the PoissonSampler.
withRange(double, double) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache: Create a new PoissonSamplerCache with the given range reusing the current cache values.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.CollectionSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.CombinationSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.DiscreteProbabilityCollectionSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ChengBetaSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.FastLoadedDiceRollerDiscreteSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.GaussianSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.LevySampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.LogNormalSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.StableSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.TSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.UniformLongSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.NormalizedGaussian: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.PermutationSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.BoxSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.LineSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.TetrahedronSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.TriangleSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.UnitBallSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in interface org.apache.commons.rng.sampling.SharedStateSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.UnitSphereSampler: Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.

Z

ZigguratNormalizedGaussianSampler - Class in org.apache.commons.rng.sampling.distribution: Marsaglia and Tsang "Ziggurat" method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.
ZigguratNormalizedGaussianSampler(UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
ZigguratSampler - Class in org.apache.commons.rng.sampling.distribution: Modified ziggurat method for sampling from Gaussian and exponential distributions.
ZigguratSampler.Exponential - Class in org.apache.commons.rng.sampling.distribution: Modified ziggurat method for sampling from an exponential distribution.
ZigguratSampler.NormalizedGaussian - Class in org.apache.commons.rng.sampling.distribution: Modified ziggurat method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.

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