Package | Description |
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org.apache.commons.rng.sampling |
This package provides sampling utilities.
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org.apache.commons.rng.sampling.distribution |
This package contains classes for sampling from statistical distributions.
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Modifier and Type | Method and Description |
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static CompositeSamplers.Builder<SharedStateContinuousSampler> |
CompositeSamplers.newSharedStateContinuousSamplerBuilder()
Create a new builder for a composite
SharedStateContinuousSampler . |
Modifier and Type | Class and Description |
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class |
AhrensDieterExponentialSampler
Sampling from an exponential distribution.
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class |
AhrensDieterMarsagliaTsangGammaSampler
Sampling from the gamma distribution.
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class |
BoxMullerNormalizedGaussianSampler
Box-Muller algorithm for sampling from Gaussian distribution with
mean 0 and standard deviation 1.
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class |
ChengBetaSampler
Sampling from a beta distribution.
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class |
ContinuousUniformSampler
Sampling from a uniform distribution.
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class |
GaussianSampler
Sampling from a Gaussian distribution with given mean and
standard deviation.
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class |
InverseTransformContinuousSampler
Distribution sampler that uses the
inversion method.
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class |
InverseTransformParetoSampler
Sampling from a Pareto distribution.
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class |
LevySampler
Sampling from a Lévy distribution.
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class |
LogNormalSampler
Sampling from a log-normal distribution.
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class |
MarsagliaNormalizedGaussianSampler
Marsaglia polar method for sampling from a Gaussian distribution
with mean 0 and standard deviation 1.
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class |
StableSampler
Samples from a stable distribution.
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class |
TSampler
Sampling from a T distribution.
|
class |
ZigguratNormalizedGaussianSampler
Marsaglia and Tsang "Ziggurat" method for sampling from a Gaussian
distribution with mean 0 and standard deviation 1.
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class |
ZigguratSampler
Modified ziggurat method for sampling from Gaussian and exponential distributions.
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static class |
ZigguratSampler.Exponential
Modified ziggurat method for sampling from an exponential distribution.
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static class |
ZigguratSampler.NormalizedGaussian
Modified ziggurat method for sampling from a Gaussian distribution with
mean 0 and standard deviation 1.
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Modifier and Type | Method and Description |
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static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> |
MarsagliaNormalizedGaussianSampler.of(UniformRandomProvider rng)
Create a new normalised Gaussian sampler.
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static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> |
BoxMullerNormalizedGaussianSampler.of(UniformRandomProvider rng)
Create a new normalised Gaussian sampler.
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static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> |
ZigguratNormalizedGaussianSampler.of(UniformRandomProvider rng)
Create a new normalised Gaussian sampler.
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Modifier and Type | Method and Description |
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static SharedStateContinuousSampler |
LogNormalSampler.of(NormalizedGaussianSampler gaussian,
double mu,
double sigma)
Create a new log-normal distribution sampler.
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static SharedStateContinuousSampler |
GaussianSampler.of(NormalizedGaussianSampler normalized,
double mean,
double standardDeviation)
Create a new normalised Gaussian sampler.
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static SharedStateContinuousSampler |
InverseTransformContinuousSampler.of(UniformRandomProvider rng,
ContinuousInverseCumulativeProbabilityFunction function)
Create a new inverse-transform continuous sampler.
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static SharedStateContinuousSampler |
AhrensDieterExponentialSampler.of(UniformRandomProvider rng,
double mean)
Create a new exponential distribution sampler.
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static SharedStateContinuousSampler |
InverseTransformParetoSampler.of(UniformRandomProvider rng,
double scale,
double shape)
Creates a new Pareto distribution sampler.
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static SharedStateContinuousSampler |
ChengBetaSampler.of(UniformRandomProvider rng,
double alpha,
double beta)
Creates a new beta distribution sampler.
|
static SharedStateContinuousSampler |
AhrensDieterMarsagliaTsangGammaSampler.of(UniformRandomProvider rng,
double alpha,
double theta)
Creates a new gamma distribution sampler.
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static SharedStateContinuousSampler |
ContinuousUniformSampler.of(UniformRandomProvider rng,
double lo,
double hi)
Creates a new continuous uniform distribution sampler.
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static SharedStateContinuousSampler |
ContinuousUniformSampler.of(UniformRandomProvider rng,
double lo,
double hi,
boolean excludeBounds)
Creates a new continuous uniform distribution sampler.
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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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
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 |
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.
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