Uses of Interface
org.apache.commons.rng.sampling.distribution.SharedStateContinuousSampler
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Packages that use SharedStateContinuousSampler 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. -
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Uses of SharedStateContinuousSampler in org.apache.commons.rng.sampling
Classes in org.apache.commons.rng.sampling that implement SharedStateContinuousSampler Modifier and Type Class Description private static class
CompositeSamplers.SharedStateContinuousSamplerFactory.CompositeSharedStateContinuousSampler
A composite continuous sampler with shared state support.Methods in org.apache.commons.rng.sampling that return SharedStateContinuousSampler Modifier and Type Method Description SharedStateContinuousSampler
CompositeSamplers.SharedStateContinuousSamplerFactory. createSampler(DiscreteSampler discreteSampler, java.util.List<SharedStateContinuousSampler> samplers)
Methods in org.apache.commons.rng.sampling that return types with arguments of type SharedStateContinuousSampler Modifier and Type Method Description static CompositeSamplers.Builder<SharedStateContinuousSampler>
CompositeSamplers. newSharedStateContinuousSamplerBuilder()
Create a new builder for a compositeSharedStateContinuousSampler
.Method parameters in org.apache.commons.rng.sampling with type arguments of type SharedStateContinuousSampler Modifier and Type Method Description SharedStateContinuousSampler
CompositeSamplers.SharedStateContinuousSamplerFactory. createSampler(DiscreteSampler discreteSampler, java.util.List<SharedStateContinuousSampler> samplers)
Constructor parameters in org.apache.commons.rng.sampling with type arguments of type SharedStateContinuousSampler Constructor Description CompositeSharedStateContinuousSampler(SharedStateDiscreteSampler discreteSampler, java.util.List<SharedStateContinuousSampler> samplers)
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Uses of SharedStateContinuousSampler in org.apache.commons.rng.sampling.distribution
Classes in org.apache.commons.rng.sampling.distribution that implement SharedStateContinuousSampler Modifier and Type Class Description class
AhrensDieterExponentialSampler
Sampling from an exponential distribution.class
AhrensDieterMarsagliaTsangGammaSampler
Sampling from the gamma distribution.private static class
AhrensDieterMarsagliaTsangGammaSampler.AhrensDieterGammaSampler
Class to sample from the Gamma distribution when0 < alpha < 1
.private static class
AhrensDieterMarsagliaTsangGammaSampler.BaseGammaSampler
Base class for a sampler from the Gamma distribution.private static class
AhrensDieterMarsagliaTsangGammaSampler.MarsagliaTsangGammaSampler
Class to sample from the Gamma distribution when thealpha >= 1
.class
BoxMullerNormalizedGaussianSampler
Box-Muller algorithm for sampling from Gaussian distribution with mean 0 and standard deviation 1.class
ChengBetaSampler
Sampling from a beta distribution.private static class
ChengBetaSampler.BaseChengBetaSampler
Base class to implement Cheng's algorithms for the beta distribution.private static class
ChengBetaSampler.ChengBBBetaSampler
Computes one sample using Cheng's BB algorithm, when beta distributionalpha
andbeta
shape parameters are both larger than 1.private static class
ChengBetaSampler.ChengBCBetaSampler
Computes one sample using Cheng's BC algorithm, when at least one of beta distributionalpha
orbeta
shape parameters is smaller than 1.class
ContinuousUniformSampler
Sampling from a uniform distribution.private static class
ContinuousUniformSampler.OpenIntervalContinuousUniformSampler
Specialization to sample from an open interval(lo, hi)
.class
GaussianSampler
Sampling from a Gaussian distribution with given mean and standard deviation.class
InverseTransformContinuousSampler
Distribution sampler that uses the inversion method.class
InverseTransformParetoSampler
Sampling from a Pareto distribution.class
LevySampler
Sampling from a Lévy distribution.class
LogNormalSampler
Sampling from a log-normal distribution.class
MarsagliaNormalizedGaussianSampler
Marsaglia polar method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.class
StableSampler
Samples from a stable distribution.(package private) static class
StableSampler.Alpha1CMSStableSampler
Implement the stable distribution case:alpha == 1
andbeta != 0
.private static class
StableSampler.BaseStableSampler
Base class for implementations of a stable distribution that requires an exponential random deviate.(package private) static class
StableSampler.Beta0CMSStableSampler
Implement the generic stable distribution case:alpha < 2
andbeta == 0
.(package private) static class
StableSampler.Beta0WeronStableSampler
Implement the generic stable distribution case:alpha < 2
andbeta == 0
.private static class
StableSampler.CauchyStableSampler
Implement thealpha = 1
andbeta = 0
stable distribution case (Cauchy distribution).(package private) static class
StableSampler.CMSStableSampler
Implement the generic stable distribution case:alpha < 2
andbeta != 0
.private static class
StableSampler.GaussianStableSampler
Implement thealpha = 2
stable distribution case (Gaussian distribution).private static class
StableSampler.LevyStableSampler
Implement thealpha = 0.5
andbeta = 1
stable distribution case (Levy distribution).private static class
StableSampler.TransformedStableSampler
Class for implementations of a stable distribution transformed by scale and location.(package private) static class
StableSampler.WeronStableSampler
Implement the generic stable distribution case:alpha < 2
andbeta != 0
.class
TSampler
Sampling from a T distribution.private static class
TSampler.NormalTSampler
Sample from a t-distribution using a normal distribution.private static class
TSampler.StudentsTSampler
Sample from a t-distribution using Bailey's algorithm.class
ZigguratNormalizedGaussianSampler
Marsaglia and Tsang "Ziggurat" method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.class
ZigguratSampler
Modified ziggurat method for sampling from Gaussian and exponential distributions.static class
ZigguratSampler.Exponential
Modified ziggurat method for sampling from an exponential distribution.private static class
ZigguratSampler.Exponential.ExponentialMean
Specialisation which multiplies the standard exponential result by a specified mean.static class
ZigguratSampler.NormalizedGaussian
Modified ziggurat method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.Fields in org.apache.commons.rng.sampling.distribution declared as SharedStateContinuousSampler Modifier and Type Field Description private SharedStateContinuousSampler
AhrensDieterMarsagliaTsangGammaSampler. delegate
The appropriate gamma sampler for the parameters.private SharedStateContinuousSampler
ChengBetaSampler. delegate
The appropriate beta sampler for the parameters.private SharedStateContinuousSampler
LargeMeanPoissonSampler. exponential
Exponential.private SharedStateContinuousSampler
ZigguratSampler.NormalizedGaussian. exponential
Exponential sampler used for the long tail.private SharedStateContinuousSampler
GeometricSampler.GeometricExponentialSampler. exponentialSampler
The related exponential sampler for the geometric distribution.private SharedStateContinuousSampler
LargeMeanPoissonSampler. gaussian
Gaussian.private SharedStateContinuousSampler
DirichletSampler.SymmetricDirichletSampler. sampler
Sampler for the categories.private SharedStateContinuousSampler[]
DirichletSampler.GeneralDirichletSampler. samplers
Samplers for each category.Methods in org.apache.commons.rng.sampling.distribution with type parameters of type SharedStateContinuousSampler Modifier and Type Method Description static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler>
SBoxMullerNormalizedGaussianSampler. of(UniformRandomProvider rng)
Create a new normalised Gaussian sampler.static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler>
SMarsagliaNormalizedGaussianSampler. of(UniformRandomProvider rng)
Create a new normalised Gaussian sampler.static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler>
SZigguratNormalizedGaussianSampler. of(UniformRandomProvider rng)
Create a new normalised Gaussian sampler.Methods in org.apache.commons.rng.sampling.distribution that return SharedStateContinuousSampler Modifier and Type Method Description private static SharedStateContinuousSampler
DirichletSampler. createSampler(UniformRandomProvider rng, double alpha)
Creates a gamma sampler for a category with the given concentration parameter.static SharedStateContinuousSampler
AhrensDieterExponentialSampler. of(UniformRandomProvider rng, double mean)
Create a new exponential distribution sampler.static SharedStateContinuousSampler
AhrensDieterMarsagliaTsangGammaSampler. of(UniformRandomProvider rng, double alpha, double theta)
Creates a new gamma distribution sampler.static SharedStateContinuousSampler
ChengBetaSampler. of(UniformRandomProvider rng, double alpha, double beta)
Creates a new beta distribution sampler.static SharedStateContinuousSampler
ContinuousUniformSampler. of(UniformRandomProvider rng, double lo, double hi)
Creates a new continuous uniform distribution sampler.static SharedStateContinuousSampler
ContinuousUniformSampler. of(UniformRandomProvider rng, double lo, double hi, boolean excludeBounds)
Creates a new continuous uniform distribution sampler.static SharedStateContinuousSampler
GaussianSampler. of(NormalizedGaussianSampler normalized, double mean, double standardDeviation)
Create a new normalised Gaussian sampler.static SharedStateContinuousSampler
InverseTransformContinuousSampler. of(UniformRandomProvider rng, ContinuousInverseCumulativeProbabilityFunction function)
Create a new inverse-transform continuous sampler.static SharedStateContinuousSampler
InverseTransformParetoSampler. of(UniformRandomProvider rng, double scale, double shape)
Creates a new Pareto distribution sampler.static SharedStateContinuousSampler
LogNormalSampler. of(NormalizedGaussianSampler gaussian, double mu, double sigma)
Create a new log-normal distribution sampler.SharedStateContinuousSampler
AhrensDieterExponentialSampler. 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.SharedStateContinuousSampler
AhrensDieterMarsagliaTsangGammaSampler.AhrensDieterGammaSampler. withUniformRandomProvider(UniformRandomProvider rng)
SharedStateContinuousSampler
AhrensDieterMarsagliaTsangGammaSampler.MarsagliaTsangGammaSampler. withUniformRandomProvider(UniformRandomProvider rng)
SharedStateContinuousSampler
AhrensDieterMarsagliaTsangGammaSampler. 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.SharedStateContinuousSampler
BoxMullerNormalizedGaussianSampler. 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.SharedStateContinuousSampler
ChengBetaSampler.ChengBBBetaSampler. withUniformRandomProvider(UniformRandomProvider rng)
SharedStateContinuousSampler
ChengBetaSampler.ChengBCBetaSampler. withUniformRandomProvider(UniformRandomProvider rng)
SharedStateContinuousSampler
ChengBetaSampler. 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.SharedStateContinuousSampler
ContinuousUniformSampler.OpenIntervalContinuousUniformSampler. withUniformRandomProvider(UniformRandomProvider rng)
SharedStateContinuousSampler
ContinuousUniformSampler. 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.SharedStateContinuousSampler
GaussianSampler. 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.SharedStateContinuousSampler
InverseTransformContinuousSampler. 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.SharedStateContinuousSampler
InverseTransformParetoSampler. 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.SharedStateContinuousSampler
LogNormalSampler. 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.SharedStateContinuousSampler
MarsagliaNormalizedGaussianSampler. 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.SharedStateContinuousSampler
ZigguratNormalizedGaussianSampler. 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 SharedStateContinuousSampler Constructor Description ChengBetaSampler(SharedStateContinuousSampler delegate)
GeneralDirichletSampler(UniformRandomProvider rng, SharedStateContinuousSampler[] samplers)
SymmetricDirichletSampler(UniformRandomProvider rng, int k, SharedStateContinuousSampler sampler)
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