Package org.apache.commons.rng.sampling.distribution

Distribution samplers

See: Description

Interface Summary

Interface	Description
ContinuousInverseCumulativeProbabilityFunction	Interface for a continuous distribution that can be sampled using the inversion method.
ContinuousSampler	Sampler that generates values of type double.
DiscreteInverseCumulativeProbabilityFunction	Interface for a discrete distribution that can be sampled using the inversion method.
DiscreteSampler	Sampler that generates values of type int.

Class Summary

Class	Description
AhrensDieterExponentialSampler	Sampling from an exponential distribution.
AhrensDieterMarsagliaTsangGammaSampler	Sampling from the Gamma distribution.
BoxMullerGaussianSampler	Box-Muller algorithm for sampling from a Gaussian distribution.
BoxMullerLogNormalSampler	Box-Muller algorithm for sampling from a Log normal distribution.
ChengBetaSampler	Utility class implementing Cheng's algorithms for beta distribution sampling.
ContinuousUniformSampler	Sampling from a uniform distribution.
DiscreteUniformSampler	Discrete uniform distribution sampler.
InverseTransformContinuousSampler	Distribution sampler that uses the inversion method.
InverseTransformDiscreteSampler	Distribution sampler that uses the inversion method.
InverseTransformParetoSampler	Sampling from a Pareto distribution.
PoissonSampler	Sampler for the Poisson distribution.
RejectionInversionZipfSampler	Implementation of the Zipf distribution.
SamplerBase	Base class for a sampler.

Package org.apache.commons.rng.sampling.distribution Description

Distribution samplers

This package contains classes for sampling from statistical distributions.

As of version 1.0, the code for specific distributions was adapted from the corresponding classes in the development version of "Commons Math" (in package org.apache.commons.math4.distribution).

When no specific algorithm is provided, one can still sample from any distribution, using the inverse method, as illustrated in:

• InverseTransformDiscreteSampler
• InverseTransformContinuousSampler

Algorithms are described in e.g. Luc Devroye (1986), chapter 9 and chapter 10.