Uses of Interface
org.apache.commons.rng.sampling.distribution.DiscreteSampler
Packages that use DiscreteSampler
Package
Description
This package provides sampling utilities.
This package contains classes for sampling from statistical distributions.
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Uses of DiscreteSampler in org.apache.commons.rng.sampling
Classes in org.apache.commons.rng.sampling that implement DiscreteSamplerModifier and TypeClassDescriptionprivate static class
A composite discrete sampler.private static class
A class to implement the SharedStateDiscreteSampler interface for a discrete probability sampler given a factory and the probability distribution.private static class
A composite discrete sampler with shared state support.Fields in org.apache.commons.rng.sampling declared as DiscreteSamplerModifier and TypeFieldDescriptionprotected final DiscreteSampler
CompositeSamplers.CompositeSampler.discreteSampler
Continuous sampler to choose the individual sampler to sample.private final DiscreteSampler
CompositeSamplers.SharedStateDiscreteProbabilitySampler.sampler
The sampler.Methods in org.apache.commons.rng.sampling that return DiscreteSamplerModifier and TypeMethodDescriptionCompositeSamplers.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.CompositeSamplers.DiscreteSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<DiscreteSampler> samplers) Methods in org.apache.commons.rng.sampling that return types with arguments of type DiscreteSamplerModifier and TypeMethodDescriptionCompositeSamplers.newDiscreteSamplerBuilder()
Create a new builder for a compositeDiscreteSampler
.Methods in org.apache.commons.rng.sampling with parameters of type DiscreteSamplerModifier and TypeMethodDescriptionCompositeSamplers.ContinuousSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<ContinuousSampler> samplers) CompositeSamplers.DiscreteSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<DiscreteSampler> samplers) CompositeSamplers.LongSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<LongSampler> samplers) CompositeSamplers.ObjectSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<ObjectSampler<T>> samplers) CompositeSamplers.SamplerBuilder.SamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<S> samplers) Creates a new composite sampler.CompositeSamplers.SharedStateContinuousSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<SharedStateContinuousSampler> samplers) CompositeSamplers.SharedStateDiscreteSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<SharedStateDiscreteSampler> samplers) CompositeSamplers.SharedStateLongSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<SharedStateLongSampler> samplers) CompositeSamplers.SharedStateObjectSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<SharedStateObjectSampler<T>> samplers) Method parameters in org.apache.commons.rng.sampling with type arguments of type DiscreteSamplerModifier and TypeMethodDescriptionCompositeSamplers.DiscreteSamplerFactory.createSampler
(DiscreteSampler discreteSampler, List<DiscreteSampler> samplers) Constructors in org.apache.commons.rng.sampling with parameters of type DiscreteSamplerModifierConstructorDescription(package private)
CompositeContinuousSampler
(DiscreteSampler discreteSampler, List<ContinuousSampler> samplers) (package private)
CompositeDiscreteSampler
(DiscreteSampler discreteSampler, List<DiscreteSampler> samplers) (package private)
CompositeLongSampler
(DiscreteSampler discreteSampler, List<LongSampler> samplers) (package private)
CompositeObjectSampler
(DiscreteSampler discreteSampler, List<ObjectSampler<T>> samplers) (package private)
CompositeSampler
(DiscreteSampler discreteSampler, List<S> samplers) (package private)
SharedStateDiscreteProbabilitySampler
(DiscreteSampler sampler, CompositeSamplers.DiscreteProbabilitySamplerFactory factory, double[] probabilities) Constructor parameters in org.apache.commons.rng.sampling with type arguments of type DiscreteSamplerModifierConstructorDescription(package private)
CompositeDiscreteSampler
(DiscreteSampler discreteSampler, List<DiscreteSampler> samplers) -
Uses of DiscreteSampler in org.apache.commons.rng.sampling.distribution
Subinterfaces of DiscreteSampler in org.apache.commons.rng.sampling.distributionModifier and TypeInterfaceDescriptioninterface
Sampler that generates values of typeint
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 DiscreteSamplerModifier and TypeClassDescriptionclass
Distribution sampler that uses the Alias method.private static class
Sample from the computed tables exploiting the small power-of-two table size.class
Discrete uniform distribution sampler.private static class
Base class for a sampler from a discrete uniform distribution.private static class
Discrete uniform distribution sampler when the sample value is fixed.private static class
Discrete uniform distribution sampler when the range between lower and upper is too large to fit in a positive integer.private static class
Adds an offset to an underlying discrete sampler.private static class
Discrete uniform distribution sampler when the range is a power of 2 and greater than 1.private static class
Discrete uniform distribution sampler when the range is small enough to fit in a positive integer.class
Distribution sampler that uses the Fast Loaded Dice Roller (FLDR).private static class
Class to handle the edge case of observations in only one category.private static class
Class to implement the FLDR sample algorithm.private static class
Sample from the geometric distribution by using a related exponential distribution.private static class
Sample from the geometric distribution when the probability of success is 1.final class
Compute a sample fromn
values each with an associated probability.class
Distribution sampler that uses the inversion method.final class
Sampler for the Poisson distribution.class
Sampler for the Poisson distribution.private static class
The base class for Marsaglia-Tsang-Wang samplers.private static class
Return a fixed result for the Binomial distribution.private static class
Return an inversion result for the Binomial distribution.private static class
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
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
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
Sampler for the Poisson distribution.class
Implementation of the Zipf distribution.private static class
Implements the rejection-inversion method for the Zipf distribution.class
Sampler for the Poisson distribution.Methods in org.apache.commons.rng.sampling.distribution that return DiscreteSamplerModifier and TypeMethodDescriptionPoissonSamplerCache.createPoissonSampler
(UniformRandomProvider rng, double mean) Deprecated.
PoissonSamplerCache.createSharedStateSampler(UniformRandomProvider, double)
.