All Classes

Class	Description
AbstractWell	This abstract class implements the WELL class of pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
AbstractWell.IndexTable	Inner class used to store the indirection index table which is fixed for a given type of WELL class of pseudo-random number generator.
AhrensDieterExponentialSampler	Sampling from an exponential distribution.
AhrensDieterMarsagliaTsangGammaSampler	Sampling from the gamma distribution.
AliasMethodDiscreteSampler	Distribution sampler that uses the Alias method.
ArraySampler	Utilities for shuffling an array in-place.
BaseProvider	Base class with default implementation for common methods.
BoxMullerGaussianSampler	Deprecated. Since version 1.1.
BoxMullerLogNormalSampler	Deprecated. Since version 1.1.
BoxMullerNormalizedGaussianSampler	Box-Muller algorithm for sampling from Gaussian distribution with mean 0 and standard deviation 1.
BoxSampler	Generate points uniformly distributed within a n-dimension box (hyperrectangle).
ChengBetaSampler	Sampling from a beta distribution.
CollectionSampler<T>	Sampling from a Collection.
CombinationSampler	Class for representing combinations of a sequence of integers.
CompositeSamplers	Factory class to create a sampler that combines sampling from multiple samplers.
CompositeSamplers.Builder<S>	Builds a composite sampler.
CompositeSamplers.DiscreteProbabilitySampler	The DiscreteProbabilitySampler class defines implementations that sample from a user-defined discrete probability distribution.
CompositeSamplers.DiscreteProbabilitySamplerFactory	A factory for creating a sampler of a user-defined discrete probability distribution.
ContinuousInverseCumulativeProbabilityFunction	Interface for a continuous distribution that can be sampled using the inversion method.
ContinuousSampler	Sampler that generates values of type double.
ContinuousUniformSampler	Sampling from a uniform distribution.
DirichletSampler	Sampling from a Dirichlet distribution.
DiscreteInverseCumulativeProbabilityFunction	Interface for a discrete distribution that can be sampled using the inversion method.
DiscreteProbabilityCollectionSampler<T>	Sampling from a collection of items with user-defined probabilities.
DiscreteSampler	Sampler that generates values of type int.
DiscreteUniformSampler	Discrete uniform distribution sampler.
DotyHumphreySmallFastCounting32	Implement the Small, Fast, Counting (SFC) 32-bit generator of Chris Doty-Humphrey.
DotyHumphreySmallFastCounting64	Implement the Small, Fast, Counting (SFC) 64-bit generator of Chris Doty-Humphrey.
FastLoadedDiceRollerDiscreteSampler	Distribution sampler that uses the Fast Loaded Dice Roller (FLDR).
GaussianSampler	Sampling from a Gaussian distribution with given mean and standard deviation.
GeometricSampler	Sampling from a geometric distribution.
GuideTableDiscreteSampler	Compute a sample from n values each with an associated probability.
IntProvider	Base class for all implementations that provide an int-based source randomness.
InverseTransformContinuousSampler	Distribution sampler that uses the inversion method.
InverseTransformDiscreteSampler	Distribution sampler that uses the inversion method.
InverseTransformParetoSampler	Sampling from a Pareto distribution.
ISAACRandom	A fast cryptographic pseudo-random number generator.
JDKRandom	A provider that uses the Random.nextInt() method of the JDK's Random class as the source of randomness.
JDKRandomBridge	Subclass of Random that delegates to a RestorableUniformRandomProvider instance but will otherwise rely on the base class for generating all the random types.
JDKRandomWrapper	Wraps a Random instance to implement UniformRandomProvider.
JenkinsSmallFast32	Implement Bob Jenkins's small fast (JSF) 32-bit generator.
JenkinsSmallFast64	Implement Bob Jenkins's small fast (JSF) 64-bit generator.
JumpableUniformRandomProvider	Applies to generators that can be advanced a large number of steps of the output sequence in a single operation.
KempSmallMeanPoissonSampler	Sampler for the Poisson distribution.
KISSRandom	Port from Marsaglia's "KISS" algorithm.
L128X1024Mix	A 64-bit all purpose generator.
L128X128Mix	A 64-bit all purpose generator.
L128X256Mix	A 64-bit all purpose generator.
L32X64Mix	A 32-bit all purpose generator.
L64X1024Mix	A 64-bit all purpose generator.
L64X128Mix	A 64-bit all purpose generator.
L64X128StarStar	A 64-bit all purpose generator.
L64X256Mix	A 64-bit all purpose generator.
LargeMeanPoissonSampler	Sampler for the Poisson distribution.
LevySampler	Sampling from a Lévy distribution.
LineSampler	Generate points uniformly distributed on a line.
ListSampler	Sampling from a List.
LogNormalSampler	Sampling from a log-normal distribution.
LongJumpableUniformRandomProvider	Applies to generators that can be advanced a very large number of steps of the output sequence in a single operation.
LongProvider	Base class for all implementations that provide a long-based source randomness.
LongSampler	Sampler that generates values of type long.
MarsagliaNormalizedGaussianSampler	Marsaglia polar method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.
MarsagliaTsangWangDiscreteSampler	Sampler for a discrete distribution using an optimised look-up table.
MarsagliaTsangWangDiscreteSampler.Binomial	Create a sampler for the Binomial distribution.
MarsagliaTsangWangDiscreteSampler.Enumerated	Create a sampler for an enumerated distribution of n values each with an associated probability.
MarsagliaTsangWangDiscreteSampler.Poisson	Create a sampler for the Poisson distribution.
MersenneTwister	This class implements a powerful pseudo-random number generator developed by Makoto Matsumoto and Takuji Nishimura during 1996-1997.
MersenneTwister64	This class provides the 64-bits version of the originally 32-bits Mersenne Twister.
MiddleSquareWeylSequence	Middle Square Weyl Sequence Random Number Generator.
MultiplyWithCarry256	Port from Marsaglia's "Multiply-With-Carry" algorithm.
NormalizedGaussianSampler	Marker interface for a sampler that generates values from an N(0,1) Gaussian distribution.
NumberFactory	Utility for creating number types from one or two int values or one long value, or a sequence of bytes.
ObjectSampler<T>	Sampler that generates values of a specified type.
PcgMcgXshRr32	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Multiplicative Congruential Generator (MCG) combined with the XSH-RR (xorshift; random rotate) output transformation to create 32-bit output.
PcgMcgXshRs32	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Multiplicative Congruential Generator (MCG) combined with the XSH-RS (xorshift; random shift) output transformation to create 32-bit output.
PcgRxsMXs64	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Linear Congruential Generator (LCG) combined with the RXS-M-XS (random xorshift; multiply; xorshift) output transformation to create 64-bit output.
PcgXshRr32	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Linear Congruential Generator (LCG) combined with the XSH-RR (xorshift; random rotate) output transformation to create 32-bit output.
PcgXshRs32	A Permuted Congruential Generator (PCG) that is composed of a 64-bit Linear Congruential Generator (LCG) combined with the XSH-RS (xorshift; random shift) output transformation to create 32-bit output.
PermutationSampler	Class for representing permutations of a sequence of integers.
PoissonSampler	Sampler for the Poisson distribution.
PoissonSamplerCache	Create a sampler for the Poisson distribution using a cache to minimise construction cost.
RandomIntSource	Source of randomness that generates values of type int.
RandomLongSource	Source of randomness that generates values of type long.
RandomProviderDefaultState	Wraps the internal state of a generator instance.
RandomProviderState	Marker interface for objects that represents the state of a random generator.
RandomSource	This class provides the API for creating generators of random numbers.
RandomStreams	Utility for creating streams using a source of randomness.
RandomStreams.SeededObjectFactory<T>	A factory for creating objects using a seed and a using a source of randomness.
RejectionInversionZipfSampler	Implementation of the Zipf distribution.
RestorableUniformRandomProvider	Applies to generators whose internal state can be saved and restored.
SamplerBase	Deprecated. Since version 1.1.
SharedStateContinuousSampler	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	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	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>	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>	Applies to samplers that can share state between instances.
SmallMeanPoissonSampler	Sampler for the Poisson distribution.
SplitMix64	A fast RNG, with 64 bits of state, that can be used to initialize the state of other generators.
SplittableUniformRandomProvider	Applies to generators that can be split into two objects (the original and a new instance) each of which implements the same interface (and can be recursively split indefinitely).
StableSampler	Samples from a stable distribution.
TetrahedronSampler	Generate points uniformly distributed within a tetrahedron.
ThreadLocalRandomSource	This class provides a thread-local UniformRandomProvider.
TriangleSampler	Generate points uniformly distributed within a triangle.
TSampler	Sampling from a T distribution.
TwoCmres	Random number generator designed by Mark D. Overton.
UniformLongSampler	Discrete uniform distribution sampler generating values of type long.
UniformRandomProvider	Applies to generators of random number sequences that follow a uniform distribution.
UnitBallSampler	Generate coordinates uniformly distributed within the unit n-ball.
UnitSphereSampler	Generate vectors isotropically located on the surface of a sphere.
Well1024a	This class implements the WELL1024a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
Well19937a	This class implements the WELL19937a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
Well19937c	This class implements the WELL19937c pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
Well44497a	This class implements the WELL44497a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
Well44497b	This class implements the WELL44497b pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
Well512a	This class implements the WELL512a pseudo-random number generator from François Panneton, Pierre L'Ecuyer and Makoto Matsumoto.
XoRoShiRo1024PlusPlus	A large-state all-purpose 64-bit generator.
XoRoShiRo1024Star	A large-state 64-bit generator suitable for double generation.
XoRoShiRo1024StarStar	A large-state all-purpose 64-bit generator.
XoRoShiRo128Plus	A fast 64-bit generator suitable for double generation.
XoRoShiRo128PlusPlus	A fast all-purpose 64-bit generator.
XoRoShiRo128StarStar	A fast all-purpose 64-bit generator.
XoRoShiRo64Star	A fast 32-bit generator suitable for float generation.
XoRoShiRo64StarStar	A fast all-purpose 32-bit generator.
XorShift1024Star	A fast RNG implementing the XorShift1024* algorithm.
XorShift1024StarPhi	A fast RNG implementing the XorShift1024* algorithm.
XoShiRo128Plus	A fast 32-bit generator suitable for float generation.
XoShiRo128PlusPlus	A fast all-purpose 32-bit generator.
XoShiRo128StarStar	A fast all-purpose 32-bit generator.
XoShiRo256Plus	A fast 64-bit generator suitable for double generation.
XoShiRo256PlusPlus	A fast all-purpose 64-bit generator.
XoShiRo256StarStar	A fast all-purpose 64-bit generator.
XoShiRo512Plus	A fast 64-bit generator suitable for double generation.
XoShiRo512PlusPlus	A fast all-purpose generator.
XoShiRo512StarStar	A fast all-purpose generator.
ZigguratNormalizedGaussianSampler	Marsaglia and Tsang "Ziggurat" method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.
ZigguratSampler	Modified ziggurat method for sampling from Gaussian and exponential distributions.
ZigguratSampler.Exponential	Modified ziggurat method for sampling from an exponential distribution.
ZigguratSampler.NormalizedGaussian	Modified ziggurat method for sampling from a Gaussian distribution with mean 0 and standard deviation 1.