Uses of Interface
org.apache.commons.rng.sampling.distribution.SharedStateDiscreteSampler

Packages that use SharedStateDiscreteSampler

Package	Description
org.apache.commons.rng.sampling	This package provides sampling utilities.
org.apache.commons.rng.sampling.distribution	This package contains classes for sampling from statistical distributions.

Uses of SharedStateDiscreteSampler in org.apache.commons.rng.sampling

Classes in org.apache.commons.rng.sampling that implement SharedStateDiscreteSampler

Modifier and Type	Class	Description
private static class	CompositeSamplers.SharedStateDiscreteProbabilitySampler	A class to implement the SharedStateDiscreteSampler interface for a discrete probability sampler given a factory and the probability distribution.
private static class	CompositeSamplers.SharedStateDiscreteSamplerFactory.CompositeSharedStateDiscreteSampler	A composite discrete sampler with shared state support.

Fields in org.apache.commons.rng.sampling declared as SharedStateDiscreteSampler

Modifier and Type	Field	Description
private SharedStateDiscreteSampler	DiscreteProbabilityCollectionSampler.sampler	Sampler for the probabilities.

Methods in org.apache.commons.rng.sampling that return SharedStateDiscreteSampler

Modifier and Type	Method	Description
SharedStateDiscreteSampler	CompositeSamplers.SharedStateDiscreteSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<SharedStateDiscreteSampler> samplers)
private static SharedStateDiscreteSampler	DiscreteProbabilityCollectionSampler.createSampler(UniformRandomProvider rng, double[] probabilities)	Creates the sampler of the enumerated probability distribution.
private static <T> SharedStateDiscreteSampler	DiscreteProbabilityCollectionSampler.createSampler(UniformRandomProvider rng, java.util.List<T> collection, double[] probabilities)	Creates the sampler of the enumerated probability distribution.
SharedStateDiscreteSampler	CompositeSamplers.SharedStateDiscreteProbabilitySampler.withUniformRandomProvider(UniformRandomProvider rng)

Methods in org.apache.commons.rng.sampling that return types with arguments of type SharedStateDiscreteSampler

Modifier and Type	Method	Description
static CompositeSamplers.Builder<SharedStateDiscreteSampler>	CompositeSamplers.newSharedStateDiscreteSamplerBuilder()	Create a new builder for a composite SharedStateDiscreteSampler.

Method parameters in org.apache.commons.rng.sampling with type arguments of type SharedStateDiscreteSampler

Modifier and Type	Method	Description
SharedStateDiscreteSampler	CompositeSamplers.SharedStateDiscreteSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<SharedStateDiscreteSampler> samplers)

Constructors in org.apache.commons.rng.sampling with parameters of type SharedStateDiscreteSampler

Constructor	Description
CompositeSharedStateContinuousSampler(SharedStateDiscreteSampler discreteSampler, java.util.List<SharedStateContinuousSampler> samplers)
CompositeSharedStateDiscreteSampler(SharedStateDiscreteSampler discreteSampler, java.util.List<SharedStateDiscreteSampler> samplers)
CompositeSharedStateLongSampler(SharedStateDiscreteSampler discreteSampler, java.util.List<SharedStateLongSampler> samplers)
CompositeSharedStateObjectSampler(SharedStateDiscreteSampler discreteSampler, java.util.List<SharedStateObjectSampler<T>> samplers)
DiscreteProbabilityCollectionSampler(java.util.List<T> items, SharedStateDiscreteSampler sampler)

Constructor parameters in org.apache.commons.rng.sampling with type arguments of type SharedStateDiscreteSampler

Constructor	Description
CompositeSharedStateDiscreteSampler(SharedStateDiscreteSampler discreteSampler, java.util.List<SharedStateDiscreteSampler> samplers)

Uses of SharedStateDiscreteSampler in org.apache.commons.rng.sampling.distribution

Classes in org.apache.commons.rng.sampling.distribution that implement SharedStateDiscreteSampler

Modifier and Type	Class	Description
class	AliasMethodDiscreteSampler	Distribution sampler that uses the Alias method.
private static class	AliasMethodDiscreteSampler.SmallTableAliasMethodDiscreteSampler	Sample from the computed tables exploiting the small power-of-two table size.
class	DiscreteUniformSampler	Discrete uniform distribution sampler.
private static class	DiscreteUniformSampler.AbstractDiscreteUniformSampler	Base class for a sampler from a discrete uniform distribution.
private static class	DiscreteUniformSampler.FixedDiscreteUniformSampler	Discrete uniform distribution sampler when the sample value is fixed.
private static class	DiscreteUniformSampler.LargeRangeDiscreteUniformSampler	Discrete uniform distribution sampler when the range between lower and upper is too large to fit in a positive integer.
private static class	DiscreteUniformSampler.OffsetDiscreteUniformSampler	Adds an offset to an underlying discrete sampler.
private static class	DiscreteUniformSampler.PowerOf2RangeDiscreteUniformSampler	Discrete uniform distribution sampler when the range is a power of 2 and greater than 1.
private static class	DiscreteUniformSampler.SmallRangeDiscreteUniformSampler	Discrete uniform distribution sampler when the range is small enough to fit in a positive integer.
class	FastLoadedDiceRollerDiscreteSampler	Distribution sampler that uses the Fast Loaded Dice Roller (FLDR).
private static class	FastLoadedDiceRollerDiscreteSampler.FixedValueDiscreteSampler	Class to handle the edge case of observations in only one category.
private static class	FastLoadedDiceRollerDiscreteSampler.FLDRSampler	Class to implement the FLDR sample algorithm.
private static class	GeometricSampler.GeometricExponentialSampler	Sample from the geometric distribution by using a related exponential distribution.
private static class	GeometricSampler.GeometricP1Sampler	Sample from the geometric distribution when the probability of success is 1.
class	GuideTableDiscreteSampler	Compute a sample from n values each with an associated probability.
class	InverseTransformDiscreteSampler	Distribution sampler that uses the inversion method.
class	KempSmallMeanPoissonSampler	Sampler for the Poisson distribution.
class	LargeMeanPoissonSampler	Sampler for the Poisson distribution.
private static class	MarsagliaTsangWangDiscreteSampler.AbstractMarsagliaTsangWangDiscreteSampler	The base class for Marsaglia-Tsang-Wang samplers.
private static class	MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangFixedResultBinomialSampler	Return a fixed result for the Binomial distribution.
private static class	MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangInversionBinomialSampler	Return an inversion result for the Binomial distribution.
private static class	MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int16DiscreteSampler	An implementation for the sample algorithm based on the decomposition of the index in the range [0,2^30) into 5 base-64 digits with 16-bit backing storage.
private static class	MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int32DiscreteSampler	An implementation for the sample algorithm based on the decomposition of the index in the range [0,2^30) into 5 base-64 digits with 32-bit backing storage.
private static class	MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int8DiscreteSampler	An implementation for the sample algorithm based on the decomposition of the index in the range [0,2^30) into 5 base-64 digits with 8-bit backing storage.
class	PoissonSampler	Sampler for the Poisson distribution.
class	RejectionInversionZipfSampler	Implementation of the Zipf distribution.
private static class	RejectionInversionZipfSampler.RejectionInversionZipfSamplerImpl	Implements the rejection-inversion method for the Zipf distribution.
class	SmallMeanPoissonSampler	Sampler for the Poisson distribution.

Fields in org.apache.commons.rng.sampling.distribution declared as SharedStateDiscreteSampler

Modifier and Type	Field	Description
private SharedStateDiscreteSampler	DiscreteUniformSampler.delegate	The appropriate uniform sampler for the parameters.
private SharedStateDiscreteSampler	RejectionInversionZipfSampler.delegate	The implementation of the sample method.
private static SharedStateDiscreteSampler	LargeMeanPoissonSampler.NO_SMALL_MEAN_POISSON_SAMPLER	Used when there is no requirement for a small mean Poisson sampler.
private SharedStateDiscreteSampler	PoissonSampler.poissonSamplerDelegate	The internal Poisson sampler.
private SharedStateDiscreteSampler	DiscreteUniformSampler.OffsetDiscreteUniformSampler.sampler	The discrete sampler.
private SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangInversionBinomialSampler.sampler	The Binomial distribution sampler.
private SharedStateDiscreteSampler	LargeMeanPoissonSampler.smallMeanPoissonSampler	The internal Poisson sampler for the lambda fraction.

Methods in org.apache.commons.rng.sampling.distribution that return SharedStateDiscreteSampler

Modifier and Type	Method	Description
private static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Binomial.createBinomialDistributionSampler(UniformRandomProvider rng, int trials, double probabilityOfSuccess)	Creates the Binomial distribution sampler.
private static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Binomial.createBinomialDistributionSamplerFromRange(UniformRandomProvider rng, int trials, double p, boolean useInversion, double p0, int begin, int end)	Creates the Binomial distribution sampler using only the probability values for X between the begin and the end (inclusive).
private static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Poisson.createPoissonDistributionFromX0(UniformRandomProvider rng, double mean)	Creates the Poisson distribution by computing probabilities recursively from X=0.
private static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Poisson.createPoissonDistributionFromXMode(UniformRandomProvider rng, double mean)	Creates the Poisson distribution by computing probabilities recursively upward and downward from X=mode, the location of the largest p-value.
private static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.createSampler(UniformRandomProvider rng, java.lang.String distributionName, int[] prob, int offset)	Create a new instance for probabilities p(i) where the sample value x is i + offset.
SharedStateDiscreteSampler	PoissonSamplerCache.createSharedStateSampler(UniformRandomProvider rng, double mean)	Creates a new Poisson sampler.
static SharedStateDiscreteSampler	AliasMethodDiscreteSampler.of(UniformRandomProvider rng, double[] probabilities)	Creates a sampler.
static SharedStateDiscreteSampler	AliasMethodDiscreteSampler.of(UniformRandomProvider rng, double[] probabilities, int alpha)	Creates a sampler.
static SharedStateDiscreteSampler	DiscreteUniformSampler.of(UniformRandomProvider rng, int lower, int upper)	Creates a new discrete uniform distribution sampler.
static SharedStateDiscreteSampler	GeometricSampler.of(UniformRandomProvider rng, double probabilityOfSuccess)	Creates a new geometric distribution sampler.
static SharedStateDiscreteSampler	GuideTableDiscreteSampler.of(UniformRandomProvider rng, double[] probabilities)	Create a new sampler for an enumerated distribution using the given probabilities.
static SharedStateDiscreteSampler	GuideTableDiscreteSampler.of(UniformRandomProvider rng, double[] probabilities, double alpha)	Create a new sampler for an enumerated distribution using the given probabilities.
static SharedStateDiscreteSampler	InverseTransformDiscreteSampler.of(UniformRandomProvider rng, DiscreteInverseCumulativeProbabilityFunction function)	Create a new inverse-transform discrete sampler.
static SharedStateDiscreteSampler	KempSmallMeanPoissonSampler.of(UniformRandomProvider rng, double mean)	Creates a new sampler for the Poisson distribution.
static SharedStateDiscreteSampler	LargeMeanPoissonSampler.of(UniformRandomProvider rng, double mean)	Creates a new Poisson distribution sampler.
static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Binomial.of(UniformRandomProvider rng, int trials, double probabilityOfSuccess)	Creates a sampler for the Binomial distribution.
static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Enumerated.of(UniformRandomProvider rng, double[] probabilities)	Creates a sampler for an enumerated distribution of n values each with an associated probability.
static SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Poisson.of(UniformRandomProvider rng, double mean)	Creates a sampler for the Poisson distribution.
static SharedStateDiscreteSampler	PoissonSampler.of(UniformRandomProvider rng, double mean)	Creates a new Poisson distribution sampler.
static SharedStateDiscreteSampler	RejectionInversionZipfSampler.of(UniformRandomProvider rng, int numberOfElements, double exponent)	Creates a new Zipf distribution sampler.
static SharedStateDiscreteSampler	SmallMeanPoissonSampler.of(UniformRandomProvider rng, double mean)	Creates a new sampler for the Poisson distribution.
SharedStateDiscreteSampler	AliasMethodDiscreteSampler.SmallTableAliasMethodDiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	AliasMethodDiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	DiscreteUniformSampler.FixedDiscreteUniformSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	DiscreteUniformSampler.LargeRangeDiscreteUniformSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	DiscreteUniformSampler.OffsetDiscreteUniformSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	DiscreteUniformSampler.PowerOf2RangeDiscreteUniformSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	DiscreteUniformSampler.SmallRangeDiscreteUniformSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	DiscreteUniformSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	GeometricSampler.GeometricExponentialSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	GeometricSampler.GeometricP1Sampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	GuideTableDiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	InverseTransformDiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	KempSmallMeanPoissonSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	LargeMeanPoissonSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangFixedResultBinomialSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.Binomial.MarsagliaTsangWangInversionBinomialSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int16DiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int32DiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	MarsagliaTsangWangDiscreteSampler.MarsagliaTsangWangBase64Int8DiscreteSampler.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	PoissonSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	RejectionInversionZipfSampler.RejectionInversionZipfSamplerImpl.withUniformRandomProvider(UniformRandomProvider rng)
SharedStateDiscreteSampler	RejectionInversionZipfSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
SharedStateDiscreteSampler	SmallMeanPoissonSampler.withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.

Constructors in org.apache.commons.rng.sampling.distribution with parameters of type SharedStateDiscreteSampler

Constructor	Description
DiscreteUniformSampler(SharedStateDiscreteSampler delegate)	Private constructor used by to prevent partially initialized object if the construction of the delegate throws.
MarsagliaTsangWangInversionBinomialSampler(int trials, SharedStateDiscreteSampler sampler)
OffsetDiscreteUniformSampler(int offset, SharedStateDiscreteSampler sampler)
PoissonSampler(SharedStateDiscreteSampler delegate)
RejectionInversionZipfSampler(SharedStateDiscreteSampler delegate)	Private constructor used by to prevent partially initialized object if the construction of the delegate throws.