Uses of Interfaceorg.apache.commons.rng.sampling.distribution.SharedStateContinuousSampler

• Packages that use SharedStateContinuousSampler
Package Description
org.apache.commons.rng.sampling
Samplers
org.apache.commons.rng.sampling.distribution
Distribution samplers
• Uses of SharedStateContinuousSampler in org.apache.commons.rng.sampling

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 composite SharedStateContinuousSampler.
• 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.
class  BoxMullerNormalizedGaussianSampler
Box-Muller algorithm for sampling from Gaussian distribution with mean 0 and standard deviation 1.
class  ChengBetaSampler
Sampling from a beta distribution.
class  ContinuousUniformSampler
Sampling from a uniform distribution.
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.
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 distributions.
static class  ZigguratSampler.NormalizedGaussian
Modified ziggurat method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.
Methods in org.apache.commons.rng.sampling.distribution with type parameters of type SharedStateContinuousSampler
Modifier and Type Method Description
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler>S BoxMullerNormalizedGaussianSampler.of​(UniformRandomProvider rng)
Create a new normalised Gaussian sampler.
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler>S MarsagliaNormalizedGaussianSampler.of​(UniformRandomProvider rng)
Create a new normalised Gaussian sampler.
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler>S ZigguratNormalizedGaussianSampler.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
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 scale, double shape)
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.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.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.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.