A B C D F G I K L M N O P R S T U V W Z
All Classes All Packages
All Classes All Packages
All Classes All Packages
A
- add(S, double) - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.Builder
-
Adds the sampler to the composite.
- AhrensDieterExponentialSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from an exponential distribution.
- AhrensDieterExponentialSampler(UniformRandomProvider, double) - Constructor for class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler
-
Create an instance.
- AhrensDieterMarsagliaTsangGammaSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from the gamma distribution.
- AhrensDieterMarsagliaTsangGammaSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler
-
This instance delegates sampling.
- alias - Variable in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
-
The alias table.
- ALIAS_METHOD - org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler
-
Sample using the alias method (see
AliasMethodDiscreteSampler
). - AliasMethodDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution
-
Distribution sampler that uses the Alias method.
- ArraySampler - Class in org.apache.commons.rng.sampling
-
Utilities for shuffling an array in-place.
B
- BoxMullerGaussianSampler - Class in org.apache.commons.rng.sampling.distribution
-
Deprecated.Since version 1.1. Please use
BoxMullerNormalizedGaussianSampler
andGaussianSampler
instead. - BoxMullerGaussianSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.BoxMullerGaussianSampler
-
Deprecated.Create an instance.
- BoxMullerLogNormalSampler - Class in org.apache.commons.rng.sampling.distribution
-
Deprecated.Since version 1.1. Please use
LogNormalSampler
instead. - BoxMullerLogNormalSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.BoxMullerLogNormalSampler
-
Deprecated.Create an instance.
- BoxMullerNormalizedGaussianSampler - Class in org.apache.commons.rng.sampling.distribution
-
Box-Muller algorithm for sampling from Gaussian distribution with mean 0 and standard deviation 1.
- BoxMullerNormalizedGaussianSampler(UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler
-
Create an instance.
- BoxSampler - Class in org.apache.commons.rng.sampling.shape
-
Generate points uniformly distributed within a n-dimension box (hyperrectangle).
- build(UniformRandomProvider) - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.Builder
-
Builds the composite sampler.
C
- ChengBetaSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a beta distribution.
- ChengBetaSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.ChengBetaSampler
-
Creates a sampler instance.
- CollectionSampler<T> - Class in org.apache.commons.rng.sampling
-
Sampling from a
Collection
. - CollectionSampler(UniformRandomProvider, Collection<T>) - Constructor for class org.apache.commons.rng.sampling.CollectionSampler
-
Creates a sampler.
- CombinationSampler - Class in org.apache.commons.rng.sampling
-
Class for representing combinations of a sequence of integers.
- CombinationSampler(UniformRandomProvider, int, int) - Constructor for class org.apache.commons.rng.sampling.CombinationSampler
-
Creates a generator of combinations.
- CompositeSamplers - Class in org.apache.commons.rng.sampling
-
Factory class to create a sampler that combines sampling from multiple samplers.
- CompositeSamplers.Builder<S> - Interface in org.apache.commons.rng.sampling
-
Builds a composite sampler.
- CompositeSamplers.DiscreteProbabilitySampler - Enum in org.apache.commons.rng.sampling
-
The DiscreteProbabilitySampler class defines implementations that sample from a user-defined discrete probability distribution.
- CompositeSamplers.DiscreteProbabilitySamplerFactory - Interface in org.apache.commons.rng.sampling
-
A factory for creating a sampler of a user-defined discrete probability distribution.
- ContinuousInverseCumulativeProbabilityFunction - Interface in org.apache.commons.rng.sampling.distribution
-
Interface for a continuous distribution that can be sampled using the inversion method.
- ContinuousSampler - Interface in org.apache.commons.rng.sampling.distribution
-
Sampler that generates values of type
double
. - ContinuousUniformSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a uniform distribution.
- ContinuousUniformSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler
-
Create an instance.
- create(UniformRandomProvider, double[]) - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySamplerFactory
-
Creates the sampler.
- createPoissonSampler(UniformRandomProvider, double) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
- createSample(double, double) - Method in class org.apache.commons.rng.sampling.shape.LineSampler
-
Creates the sample given the random variate
u
in the interval[0, 1]
. - createSample(double, double, double) - Method in class org.apache.commons.rng.sampling.shape.TriangleSampler
-
Creates the sample given the random variates
s
andt
in the interval[0, 1]
ands + t <= 1
. - createSharedStateSampler(UniformRandomProvider, double) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
-
Creates a new Poisson sampler.
D
- DirichletSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a Dirichlet distribution.
- DiscreteInverseCumulativeProbabilityFunction - Interface in org.apache.commons.rng.sampling.distribution
-
Interface for a discrete distribution that can be sampled using the inversion method.
- DiscreteProbabilityCollectionSampler<T> - Class in org.apache.commons.rng.sampling
-
Sampling from a collection of items with user-defined probabilities.
- DiscreteProbabilityCollectionSampler(UniformRandomProvider, List<T>, double[]) - Constructor for class org.apache.commons.rng.sampling.DiscreteProbabilityCollectionSampler
-
Creates a sampler.
- DiscreteProbabilityCollectionSampler(UniformRandomProvider, Map<T, Double>) - Constructor for class org.apache.commons.rng.sampling.DiscreteProbabilityCollectionSampler
-
Creates a sampler.
- DiscreteSampler - Interface in org.apache.commons.rng.sampling.distribution
-
Sampler that generates values of type
int
. - DiscreteUniformSampler - Class in org.apache.commons.rng.sampling.distribution
-
Discrete uniform distribution sampler.
- DiscreteUniformSampler(UniformRandomProvider, int, int) - Constructor for class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler
-
This instance delegates sampling.
F
- FastLoadedDiceRollerDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution
-
Distribution sampler that uses the Fast Loaded Dice Roller (FLDR).
G
- GaussianSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a Gaussian distribution with given mean and standard deviation.
- GaussianSampler(NormalizedGaussianSampler, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.GaussianSampler
-
Create an instance.
- GeometricSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a geometric distribution.
- getK() - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
-
Gets the number of categories.
- getMaxMean() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
-
Gets the maximum mean covered by the cache.
- getMinimumCachedMean() - Static method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
-
Gets the minimum mean value that can be cached.
- getMinMean() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
-
Gets the minimum mean covered by the cache.
- GUIDE_TABLE - org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler
-
Sample using a guide table (see
GuideTableDiscreteSampler
). - GuideTableDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution
-
Compute a sample from
n
values each with an associated probability.
I
- inverseCumulativeProbability(double) - Method in interface org.apache.commons.rng.sampling.distribution.ContinuousInverseCumulativeProbabilityFunction
-
Computes the quantile function of the distribution.
- inverseCumulativeProbability(double) - Method in interface org.apache.commons.rng.sampling.distribution.DiscreteInverseCumulativeProbabilityFunction
-
Computes the quantile function of the distribution.
- InverseTransformContinuousSampler - Class in org.apache.commons.rng.sampling.distribution
-
Distribution sampler that uses the inversion method.
- InverseTransformContinuousSampler(UniformRandomProvider, ContinuousInverseCumulativeProbabilityFunction) - Constructor for class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler
-
Create an instance.
- InverseTransformDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution
-
Distribution sampler that uses the inversion method.
- InverseTransformDiscreteSampler(UniformRandomProvider, DiscreteInverseCumulativeProbabilityFunction) - Constructor for class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler
-
Create an instance.
- InverseTransformParetoSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a Pareto distribution.
- InverseTransformParetoSampler(UniformRandomProvider, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler
-
Create an instance.
- isValidRange() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
-
Checks if the cache covers a valid range of mean values.
K
- KempSmallMeanPoissonSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampler for the Poisson distribution.
L
- LargeMeanPoissonSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampler for the Poisson distribution.
- LargeMeanPoissonSampler(UniformRandomProvider, double) - Constructor for class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler
-
Create an instance.
- LevySampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a Lévy distribution.
- LineSampler - Class in org.apache.commons.rng.sampling.shape
-
Generate points uniformly distributed on a line.
- ListSampler - Class in org.apache.commons.rng.sampling
-
Sampling from a
List
. - LogNormalSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a log-normal distribution.
- LogNormalSampler(NormalizedGaussianSampler, double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.LogNormalSampler
-
Create an instance.
- LongSampler - Interface in org.apache.commons.rng.sampling.distribution
-
Sampler that generates values of type
long
. - LOOKUP_TABLE - org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler
-
Sample using an optimised look-up table (see
MarsagliaTsangWangDiscreteSampler.Enumerated
).
M
- MarsagliaNormalizedGaussianSampler - Class in org.apache.commons.rng.sampling.distribution
-
Marsaglia polar method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.
- MarsagliaNormalizedGaussianSampler(UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler
-
Create an instance.
- MarsagliaTsangWangDiscreteSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampler for a discrete distribution using an optimised look-up table.
- MarsagliaTsangWangDiscreteSampler.Binomial - Class in org.apache.commons.rng.sampling.distribution
-
Create a sampler for the Binomial distribution.
- MarsagliaTsangWangDiscreteSampler.Enumerated - Class in org.apache.commons.rng.sampling.distribution
-
Create a sampler for an enumerated distribution of
n
values each with an associated probability. - MarsagliaTsangWangDiscreteSampler.Poisson - Class in org.apache.commons.rng.sampling.distribution
-
Create a sampler for the Poisson distribution.
N
- natural(int) - Static method in class org.apache.commons.rng.sampling.PermutationSampler
-
Creates an array representing the natural number
n
. - newContinuousSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers
-
Create a new builder for a composite
ContinuousSampler
. - newDiscreteSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers
-
Create a new builder for a composite
DiscreteSampler
. - newLongSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers
-
Create a new builder for a composite
LongSampler
. - newObjectSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers
-
Create a new builder for a composite
ObjectSampler
. - newSharedStateContinuousSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers
-
Create a new builder for a composite
SharedStateContinuousSampler
. - newSharedStateDiscreteSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers
-
Create a new builder for a composite
SharedStateDiscreteSampler
. - newSharedStateLongSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers
-
Create a new builder for a composite
SharedStateLongSampler
. - newSharedStateObjectSamplerBuilder() - Static method in class org.apache.commons.rng.sampling.CompositeSamplers
-
Create a new builder for a composite
SharedStateObjectSampler
. - nextDouble() - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase
-
Deprecated.Return the next
double
value. - nextGamma(int) - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
-
Create a gamma sample for the given category.
- nextInt() - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase
-
Deprecated.Return the next
int
value. - nextInt(int) - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase
-
Deprecated.Return the next
int
value. - nextLong() - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase
-
Deprecated.Return the next
long
value. - nextVector() - Method in class org.apache.commons.rng.sampling.UnitSphereSampler
-
Deprecated.
- NormalizedGaussianSampler - Interface in org.apache.commons.rng.sampling.distribution
-
Marker interface for a sampler that generates values from an N(0,1) Gaussian distribution.
O
- ObjectSampler<T> - Interface in org.apache.commons.rng.sampling
-
Sampler that generates values of a specified type.
- of(NormalizedGaussianSampler, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.GaussianSampler
-
Create a new normalised Gaussian sampler.
- of(NormalizedGaussianSampler, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.LogNormalSampler
-
Create a new log-normal distribution sampler.
- of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler
-
Create a new normalised Gaussian sampler.
- of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler
-
Create a new normalised Gaussian sampler.
- of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
-
Create a new normalised Gaussian sampler.
- of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential
-
Create a new exponential sampler with
mean = 1
. - of(UniformRandomProvider) - Static method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.NormalizedGaussian
-
Create a new normalised Gaussian sampler.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler
-
Create a new exponential distribution sampler.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.GeometricSampler
-
Creates a new geometric distribution sampler.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler
-
Creates a new sampler for the Poisson distribution.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler
-
Creates a new Poisson distribution sampler.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.Poisson
-
Creates a sampler for the Poisson distribution.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.PoissonSampler
-
Creates a new Poisson distribution sampler.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler
-
Creates a new sampler for the Poisson distribution.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.TSampler
-
Create a new t distribution sampler.
- of(UniformRandomProvider, double) - Static method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential
-
Create a new exponential sampler with the specified
mean
. - of(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
-
Creates a sampler.
- of(UniformRandomProvider, double...) - Static method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
-
Creates a new Dirichlet distribution sampler.
- of(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.distribution.FastLoadedDiceRollerDiscreteSampler
-
Creates a sampler.
- of(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler
-
Create a new sampler for an enumerated distribution using the given
probabilities
. - of(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.Enumerated
-
Creates a sampler for an enumerated distribution of
n
values each with an associated probability. - of(UniformRandomProvider, double[], double) - Static method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler
-
Create a new sampler for an enumerated distribution using the given
probabilities
. - of(UniformRandomProvider, double[], double[]) - Static method in class org.apache.commons.rng.sampling.shape.BoxSampler
-
Create a box sampler with bounds
a
andb
. - of(UniformRandomProvider, double[], double[]) - Static method in class org.apache.commons.rng.sampling.shape.LineSampler
-
Create a line sampler with vertices
a
andb
. - of(UniformRandomProvider, double[], double[], double[]) - Static method in class org.apache.commons.rng.sampling.shape.TriangleSampler
-
Create a triangle sampler with vertices
a
,b
andc
. - of(UniformRandomProvider, double[], double[], double[], double[]) - Static method in class org.apache.commons.rng.sampling.shape.TetrahedronSampler
-
Create a tetrahedron sampler with vertices
a
,b
,c
andd
. - of(UniformRandomProvider, double[], int) - Static method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
-
Creates a sampler.
- of(UniformRandomProvider, double[], int) - Static method in class org.apache.commons.rng.sampling.distribution.FastLoadedDiceRollerDiscreteSampler
-
Creates a sampler.
- of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler
-
Creates a new gamma distribution sampler.
- of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.ChengBetaSampler
-
Creates a new beta distribution sampler.
- of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler
-
Creates a new continuous uniform distribution sampler.
- of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler
-
Creates a new Pareto distribution sampler.
- of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.LevySampler
-
Create a new Lévy distribution sampler.
- of(UniformRandomProvider, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.StableSampler
-
Creates a standardized sampler of a stable distribution with zero location and unit scale.
- of(UniformRandomProvider, double, double, boolean) - Static method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler
-
Creates a new continuous uniform distribution sampler.
- of(UniformRandomProvider, double, double, double, double) - Static method in class org.apache.commons.rng.sampling.distribution.StableSampler
-
Creates a sampler of a stable distribution.
- of(UniformRandomProvider, int) - Static method in class org.apache.commons.rng.sampling.shape.UnitBallSampler
-
Create a unit n-ball sampler for the given dimension.
- of(UniformRandomProvider, int) - Static method in class org.apache.commons.rng.sampling.UnitSphereSampler
-
Create a unit sphere sampler for the given dimension.
- of(UniformRandomProvider, int, double) - Static method in class org.apache.commons.rng.sampling.distribution.MarsagliaTsangWangDiscreteSampler.Binomial
-
Creates a sampler for the Binomial distribution.
- of(UniformRandomProvider, int, double) - Static method in class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler
-
Creates a new Zipf distribution sampler.
- of(UniformRandomProvider, int, int) - Static method in class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler
-
Creates a new discrete uniform distribution sampler.
- of(UniformRandomProvider, long[]) - Static method in class org.apache.commons.rng.sampling.distribution.FastLoadedDiceRollerDiscreteSampler
-
Creates a sampler.
- of(UniformRandomProvider, long, long) - Static method in class org.apache.commons.rng.sampling.distribution.UniformLongSampler
-
Creates a new discrete uniform distribution sampler.
- of(UniformRandomProvider, ContinuousInverseCumulativeProbabilityFunction) - Static method in class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler
-
Create a new inverse-transform continuous sampler.
- of(UniformRandomProvider, DiscreteInverseCumulativeProbabilityFunction) - Static method in class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler
-
Create a new inverse-transform discrete sampler.
- org.apache.commons.rng.sampling - package org.apache.commons.rng.sampling
-
This package provides sampling utilities.
- org.apache.commons.rng.sampling.distribution - package org.apache.commons.rng.sampling.distribution
-
This package contains classes for sampling from statistical distributions.
- org.apache.commons.rng.sampling.shape - package org.apache.commons.rng.sampling.shape
-
This package contains classes for sampling coordinates from shapes, for example a unit ball.
P
- PermutationSampler - Class in org.apache.commons.rng.sampling
-
Class for representing permutations of a sequence of integers.
- PermutationSampler(UniformRandomProvider, int, int) - Constructor for class org.apache.commons.rng.sampling.PermutationSampler
-
Creates a generator of permutations.
- PoissonSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampler for the Poisson distribution.
- PoissonSampler(UniformRandomProvider, double) - Constructor for class org.apache.commons.rng.sampling.distribution.PoissonSampler
-
This instance delegates sampling.
- PoissonSamplerCache - Class in org.apache.commons.rng.sampling.distribution
-
Create a sampler for the Poisson distribution using a cache to minimise construction cost.
- PoissonSamplerCache(double, double) - Constructor for class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
-
Create an instance.
- probability - Variable in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
-
The probability table.
R
- RejectionInversionZipfSampler - Class in org.apache.commons.rng.sampling.distribution
-
Implementation of the Zipf distribution.
- RejectionInversionZipfSampler(UniformRandomProvider, int, double) - Constructor for class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler
-
This instance delegates sampling.
- rng - Variable in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
-
Underlying source of randomness.
- rng - Variable in class org.apache.commons.rng.sampling.distribution.UniformLongSampler
-
Underlying source of randomness.
S
- sample() - Method in class org.apache.commons.rng.sampling.CollectionSampler
-
Picks one of the items from the
collection passed to the constructor
. - sample() - Method in class org.apache.commons.rng.sampling.CombinationSampler
-
Return a combination of
k
whose entries are selected randomly, without repetition, from the integers 0, 1, ...,n
-1 (inclusive). - sample() - Method in class org.apache.commons.rng.sampling.DiscreteProbabilityCollectionSampler
-
Picks one of the items from the collection passed to the constructor.
- sample() - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerGaussianSampler
-
Deprecated.Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerLogNormalSampler
-
Deprecated.Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.ChengBetaSampler
-
Creates a
double
sample. - sample() - Method in interface org.apache.commons.rng.sampling.distribution.ContinuousSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
-
Create an object sample.
- sample() - Method in interface org.apache.commons.rng.sampling.distribution.DiscreteSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.GaussianSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.LevySampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.LogNormalSampler
-
Creates a
double
sample. - sample() - Method in interface org.apache.commons.rng.sampling.distribution.LongSampler
-
Creates a
long
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler
-
Rejection inversion sampling method for a discrete, bounded Zipf distribution that is based on the method described in Wolfgang Hörmann and Gerhard Derflinger.
- sample() - Method in class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler
-
Creates an
int
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.StableSampler
-
Generate a sample from a stable distribution.
- sample() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential
-
Creates a
double
sample. - sample() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.NormalizedGaussian
-
Creates a
double
sample. - sample() - Method in interface org.apache.commons.rng.sampling.ObjectSampler
-
Create an object sample.
- sample() - Method in class org.apache.commons.rng.sampling.PermutationSampler
- sample() - Method in class org.apache.commons.rng.sampling.shape.BoxSampler
- sample() - Method in class org.apache.commons.rng.sampling.shape.LineSampler
- sample() - Method in class org.apache.commons.rng.sampling.shape.TetrahedronSampler
- sample() - Method in class org.apache.commons.rng.sampling.shape.TriangleSampler
- sample() - Method in class org.apache.commons.rng.sampling.shape.UnitBallSampler
- sample() - Method in class org.apache.commons.rng.sampling.UnitSphereSampler
- sample(UniformRandomProvider, List<T>, int) - Static method in class org.apache.commons.rng.sampling.ListSampler
-
Generates a list of size
k
whose entries are selected randomly, without repetition, from the items in the givencollection
. - SamplerBase - Class in org.apache.commons.rng.sampling.distribution
-
Deprecated.Since version 1.1. Class intended for internal use only.
- SamplerBase(UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.distribution.SamplerBase
-
Deprecated.Create an instance.
- samples() - Method in interface org.apache.commons.rng.sampling.distribution.ContinuousSampler
-
Returns an effectively unlimited stream of
double
sample values. - samples() - Method in interface org.apache.commons.rng.sampling.distribution.DiscreteSampler
-
Returns an effectively unlimited stream of
int
sample values. - samples() - Method in interface org.apache.commons.rng.sampling.distribution.LongSampler
-
Returns an effectively unlimited stream of
long
sample values. - samples() - Method in interface org.apache.commons.rng.sampling.ObjectSampler
-
Returns an effectively unlimited stream of object sample values.
- samples(long) - Method in interface org.apache.commons.rng.sampling.distribution.ContinuousSampler
-
Returns a stream producing the given
streamSize
number ofdouble
sample values. - samples(long) - Method in interface org.apache.commons.rng.sampling.distribution.DiscreteSampler
-
Returns a stream producing the given
streamSize
number ofint
sample values. - samples(long) - Method in interface org.apache.commons.rng.sampling.distribution.LongSampler
-
Returns a stream producing the given
streamSize
number oflong
sample values. - samples(long) - Method in interface org.apache.commons.rng.sampling.ObjectSampler
-
Returns a stream producing the given
streamSize
number of object sample values. - setFactory(CompositeSamplers.DiscreteProbabilitySamplerFactory) - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.Builder
-
Sets the factory to use to generate the composite's discrete sampler from the sampler weights.
- SharedStateContinuousSampler - Interface in org.apache.commons.rng.sampling.distribution
-
Sampler that generates values of type
double
and can create new instances to sample from the same state with a given source of randomness. - SharedStateDiscreteSampler - Interface in org.apache.commons.rng.sampling.distribution
-
Sampler that generates values of type
int
and can create new instances to sample from the same state with a given source of randomness. - SharedStateLongSampler - Interface in org.apache.commons.rng.sampling.distribution
-
Sampler that generates values of type
long
and can create new instances to sample from the same state with a given source of randomness. - SharedStateObjectSampler<T> - Interface in org.apache.commons.rng.sampling
-
Sampler that generates values of a specified type and can create new instances to sample from the same state with a given source of randomness.
- SharedStateSampler<R> - Interface in org.apache.commons.rng.sampling
-
Applies to samplers that can share state between instances.
- shuffle(UniformRandomProvider, boolean[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, boolean[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - shuffle(UniformRandomProvider, byte[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, byte[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - shuffle(UniformRandomProvider, char[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, char[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - shuffle(UniformRandomProvider, double[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, double[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - shuffle(UniformRandomProvider, float[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, float[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - shuffle(UniformRandomProvider, int[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, int[]) - Static method in class org.apache.commons.rng.sampling.PermutationSampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, int[], int, boolean) - Static method in class org.apache.commons.rng.sampling.PermutationSampler
-
Shuffles the entries of the given array, using the Fisher-Yates algorithm.
- shuffle(UniformRandomProvider, int[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - shuffle(UniformRandomProvider, long[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, long[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - shuffle(UniformRandomProvider, short[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, short[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - shuffle(UniformRandomProvider, List<T>) - Static method in class org.apache.commons.rng.sampling.ListSampler
-
Shuffles the entries of the given array, using the Fisher-Yates algorithm.
- shuffle(UniformRandomProvider, List<T>, int, boolean) - Static method in class org.apache.commons.rng.sampling.ListSampler
-
Shuffles the entries of the given array, using the Fisher-Yates algorithm.
- shuffle(UniformRandomProvider, T[]) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array.
- shuffle(UniformRandomProvider, T[], int, int) - Static method in class org.apache.commons.rng.sampling.ArraySampler
-
Shuffles the entries of the given array in the range
[from, to)
. - size() - Method in interface org.apache.commons.rng.sampling.CompositeSamplers.Builder
-
Return the number of samplers in the composite.
- SmallMeanPoissonSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampler for the Poisson distribution.
- SmallMeanPoissonSampler(UniformRandomProvider, double) - Constructor for class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler
-
Create an instance.
- StableSampler - Class in org.apache.commons.rng.sampling.distribution
-
Samples from a stable distribution.
- symmetric(UniformRandomProvider, int, double) - Static method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
-
Creates a new symmetric Dirichlet distribution sampler using the same concentration parameter for each category.
T
- TetrahedronSampler - Class in org.apache.commons.rng.sampling.shape
-
Generate points uniformly distributed within a tetrahedron.
- toString() - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerGaussianSampler
-
Deprecated.
- toString() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerLogNormalSampler
-
Deprecated.
- toString() - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.ChengBetaSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.GaussianSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.LevySampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.LogNormalSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.PoissonSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.SamplerBase
-
Deprecated.
- toString() - Method in class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.StableSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.TSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.UniformLongSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
- toString() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential
- toString() - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.NormalizedGaussian
- TriangleSampler - Class in org.apache.commons.rng.sampling.shape
-
Generate points uniformly distributed within a triangle.
- TSampler - Class in org.apache.commons.rng.sampling.distribution
-
Sampling from a T distribution.
U
- UniformLongSampler - Class in org.apache.commons.rng.sampling.distribution
-
Discrete uniform distribution sampler generating values of type
long
. - UnitBallSampler - Class in org.apache.commons.rng.sampling.shape
-
Generate coordinates uniformly distributed within the unit n-ball.
- UnitBallSampler() - Constructor for class org.apache.commons.rng.sampling.shape.UnitBallSampler
-
Create an instance.
- UnitSphereSampler - Class in org.apache.commons.rng.sampling
-
Generate vectors isotropically located on the surface of a sphere.
- UnitSphereSampler(int, UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.UnitSphereSampler
-
Deprecated.
V
- valueOf(String) - Static method in enum org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler
-
Returns the enum constant of this type with the specified name.
- values() - Static method in enum org.apache.commons.rng.sampling.CompositeSamplers.DiscreteProbabilitySampler
-
Returns an array containing the constants of this enum type, in the order they are declared.
W
- withinRange(double) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
-
Check if the mean is within the range where the cache can minimise the construction cost of the
PoissonSampler
. - withRange(double, double) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSamplerCache
-
Create a new
PoissonSamplerCache
with the given range reusing the current cache values. - withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.CollectionSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.CombinationSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.DiscreteProbabilityCollectionSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterExponentialSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.AhrensDieterMarsagliaTsangGammaSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.AliasMethodDiscreteSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.BoxMullerNormalizedGaussianSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ChengBetaSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.DirichletSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.DiscreteUniformSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.FastLoadedDiceRollerDiscreteSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.GaussianSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.GuideTableDiscreteSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.InverseTransformParetoSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.KempSmallMeanPoissonSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.LevySampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.LogNormalSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.MarsagliaNormalizedGaussianSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.PoissonSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.RejectionInversionZipfSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.SmallMeanPoissonSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.StableSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.TSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.UniformLongSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.Exponential
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.distribution.ZigguratSampler.NormalizedGaussian
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.PermutationSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.BoxSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.LineSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.TetrahedronSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.TriangleSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.shape.UnitBallSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in interface org.apache.commons.rng.sampling.SharedStateSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
- withUniformRandomProvider(UniformRandomProvider) - Method in class org.apache.commons.rng.sampling.UnitSphereSampler
-
Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.
Z
- ZigguratNormalizedGaussianSampler - Class in org.apache.commons.rng.sampling.distribution
-
Marsaglia and Tsang "Ziggurat" method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.
- ZigguratNormalizedGaussianSampler(UniformRandomProvider) - Constructor for class org.apache.commons.rng.sampling.distribution.ZigguratNormalizedGaussianSampler
-
Create an instance.
- ZigguratSampler - Class in org.apache.commons.rng.sampling.distribution
-
Modified ziggurat method for sampling from Gaussian and exponential distributions.
- ZigguratSampler.Exponential - Class in org.apache.commons.rng.sampling.distribution
-
Modified ziggurat method for sampling from an exponential distribution.
- ZigguratSampler.NormalizedGaussian - Class in org.apache.commons.rng.sampling.distribution
-
Modified ziggurat method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.
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