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

Packages that use DiscreteSampler

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 DiscreteSampler in org.apache.commons.rng.sampling

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

Modifier and Type	Class	Description
private static class	CompositeSamplers.DiscreteSamplerFactory.CompositeDiscreteSampler	A composite discrete sampler.
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 DiscreteSampler

Modifier and Type	Field	Description
protected DiscreteSampler	CompositeSamplers.CompositeSampler.discreteSampler	Continuous sampler to choose the individual sampler to sample.
private DiscreteSampler	CompositeSamplers.SharedStateDiscreteProbabilitySampler.sampler	The sampler.

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

Modifier and Type	Method	Description
DiscreteSampler	CompositeSamplers.DiscreteProbabilitySamplerFactory.create(UniformRandomProvider rng, double[] probabilities)	Creates the sampler.
private DiscreteSampler	CompositeSamplers.SamplerBuilder.createDiscreteSampler(UniformRandomProvider rng, double[] weights)	Creates the discrete sampler of the enumerated probability distribution.
DiscreteSampler	CompositeSamplers.DiscreteSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<DiscreteSampler> samplers)

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

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

Methods in org.apache.commons.rng.sampling with parameters of type DiscreteSampler

Modifier and Type	Method	Description
ContinuousSampler	CompositeSamplers.ContinuousSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<ContinuousSampler> samplers)
DiscreteSampler	CompositeSamplers.DiscreteSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<DiscreteSampler> samplers)
LongSampler	CompositeSamplers.LongSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<LongSampler> samplers)
ObjectSampler<T>	CompositeSamplers.ObjectSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<ObjectSampler<T>> samplers)
S	CompositeSamplers.SamplerBuilder.SamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<S> samplers)	Creates a new composite sampler.
SharedStateContinuousSampler	CompositeSamplers.SharedStateContinuousSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<SharedStateContinuousSampler> samplers)
SharedStateDiscreteSampler	CompositeSamplers.SharedStateDiscreteSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<SharedStateDiscreteSampler> samplers)
SharedStateLongSampler	CompositeSamplers.SharedStateLongSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<SharedStateLongSampler> samplers)
SharedStateObjectSampler<T>	CompositeSamplers.SharedStateObjectSamplerFactory.createSampler(DiscreteSampler discreteSampler, java.util.List<SharedStateObjectSampler<T>> samplers)

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

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

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

Constructor	Description
CompositeContinuousSampler(DiscreteSampler discreteSampler, java.util.List<ContinuousSampler> samplers)
CompositeDiscreteSampler(DiscreteSampler discreteSampler, java.util.List<DiscreteSampler> samplers)
CompositeLongSampler(DiscreteSampler discreteSampler, java.util.List<LongSampler> samplers)
CompositeObjectSampler(DiscreteSampler discreteSampler, java.util.List<ObjectSampler<T>> samplers)
CompositeSampler(DiscreteSampler discreteSampler, java.util.List<S> samplers)
SharedStateDiscreteProbabilitySampler(DiscreteSampler sampler, CompositeSamplers.DiscreteProbabilitySamplerFactory factory, double[] probabilities)

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

Constructor	Description
CompositeDiscreteSampler(DiscreteSampler discreteSampler, java.util.List<DiscreteSampler> samplers)

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

Subinterfaces of DiscreteSampler in org.apache.commons.rng.sampling.distribution

Modifier and Type	Interface	Description
interface	SharedStateDiscreteSampler	Sampler that generates values of type int and can create new instances to sample from the same state with a given source of randomness.

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

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.

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

Modifier and Type	Method	Description
DiscreteSampler	PoissonSamplerCache.createPoissonSampler(UniformRandomProvider rng, double mean)	Deprecated. Use PoissonSamplerCache.createSharedStateSampler(UniformRandomProvider, double).