All Classes

Class	Description
AhrensDieterExponentialSampler	Sampling from an exponential distribution.
AhrensDieterMarsagliaTsangGammaSampler	Sampling from the gamma distribution.
AliasMethodDiscreteSampler	Distribution sampler that uses the Alias method.
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.
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.
InverseTransformContinuousSampler	Distribution sampler that uses the inversion method.
InverseTransformDiscreteSampler	Distribution sampler that uses the inversion method.
InverseTransformParetoSampler	Sampling from a Pareto distribution.
KempSmallMeanPoissonSampler	Sampler for the Poisson distribution.
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.
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.
NormalizedGaussianSampler	Marker interface for a sampler that generates values from an N(0,1) Gaussian distribution.
ObjectSampler<T>	Sampler that generates values of a specified type.
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.
RejectionInversionZipfSampler	Implementation of the Zipf distribution.
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.
StableSampler	Samples from a stable distribution.
TetrahedronSampler	Generate points uniformly distributed within a tetrahedron.
TriangleSampler	Generate points uniformly distributed within a triangle.
TSampler	Sampling from a T distribution.
UniformLongSampler	Discrete uniform distribution sampler generating values of type long.
UnitBallSampler	Generate coordinates uniformly distributed within the unit n-ball.
UnitSphereSampler	Generate vectors isotropically located on the surface of a sphere.
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.