Package | Description |
---|---|
org.apache.commons.rng.sampling.distribution |
Distribution samplers
|
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 |
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 |
ZigguratNormalizedGaussianSampler |
Marsaglia and Tsang "Ziggurat" method for sampling from a Gaussian
distribution with mean 0 and standard deviation 1.
|
Modifier and Type | Method | Description |
---|---|---|
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> |
BoxMullerNormalizedGaussianSampler.of(org.apache.commons.rng.UniformRandomProvider rng) |
Create a new normalised Gaussian sampler.
|
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> |
MarsagliaNormalizedGaussianSampler.of(org.apache.commons.rng.UniformRandomProvider rng) |
Create a new normalised Gaussian sampler.
|
static <S extends NormalizedGaussianSampler & SharedStateContinuousSampler> |
ZigguratNormalizedGaussianSampler.of(org.apache.commons.rng.UniformRandomProvider rng) |
Create a new normalised Gaussian sampler.
|
Modifier and Type | Method | Description |
---|---|---|
static SharedStateContinuousSampler |
AhrensDieterExponentialSampler.of(org.apache.commons.rng.UniformRandomProvider rng,
double mean) |
Create a new exponential distribution sampler.
|
static SharedStateContinuousSampler |
AhrensDieterMarsagliaTsangGammaSampler.of(org.apache.commons.rng.UniformRandomProvider rng,
double alpha,
double theta) |
Creates a new gamma distribution sampler.
|
static SharedStateContinuousSampler |
ChengBetaSampler.of(org.apache.commons.rng.UniformRandomProvider rng,
double alpha,
double beta) |
Creates a new beta distribution sampler.
|
static SharedStateContinuousSampler |
ContinuousUniformSampler.of(org.apache.commons.rng.UniformRandomProvider rng,
double lo,
double hi) |
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(org.apache.commons.rng.UniformRandomProvider rng,
ContinuousInverseCumulativeProbabilityFunction function) |
Create a new inverse-transform continuous sampler.
|
static SharedStateContinuousSampler |
InverseTransformParetoSampler.of(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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(org.apache.commons.rng.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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