Package umontreal.iro.lecuyer.randvar

Class Summary

Class	Description
BernoulliGen	This class implements random variate generators for the Bernoulli distribution (see class BernoulliDist).
BetaGen	This class implements random variate generators with the beta distribution with shape parameters α > 0 and β > 0, over the interval (a, b), where a < b.
BetaRejectionLoglogisticGen	Implements Beta random variate generators using the rejection method with log-logistic envelopes.
BetaStratifiedRejectionGen	This class implements Beta random variate generators using the stratified rejection/patchwork rejection method.
BetaSymmetricalBestGen	This class implements symmetrical beta random variate generators using Devroye's one-liner method.
BetaSymmetricalGen	This class implements random variate generators with the symmetrical beta distribution with shape parameters α = β, over the interval (0, 1).
BetaSymmetricalPolarGen	This class implements symmetrical beta random variate generators using Ulrich's polar method.
BinomialConvolutionGen	Implements binomial random variate generators using the convolution method.
BinomialGen	This class implements random variate generators for the binomial distribution.
CauchyGen	This class implements random variate generators for the Cauchy distribution.
ChiGen	This class implements random variate generators for the chi distribution.
ChiRatioOfUniformsGen	This class implements Chi random variate generators using the ratio of uniforms method with shift.
ChiSquareGen	This class implements random variate generators with the chi square distribution with n > 0 degrees of freedom.
ChiSquareNoncentralGamGen	This class implements noncentral chi square random variate generators using the additive property of the noncentral chi square distribution.
ChiSquareNoncentralGen	This class implements random variate generators for the noncentral chi square distribution with ν degrees of freedom and noncentrality parameter λ.
ChiSquareNoncentralPoisGen	This class implements noncentral chi square random variate generators using Poisson and central chi square generators.
ErlangConvolutionGen	This class implements Erlang random variate generators using the convolution method.
ErlangGen	This class implements random variate generators for the Erlang distribution with parameters k > 0 and λ > 0.
ExponentialGen	This class implements random variate generators for the exponential distribution.
ExtremeValueGen	Deprecated
FatigueLifeGen	This class implements random variate generators for the fatigue life distribution with location parameter μ, scale parameter β and shape parameter γ.
FisherFGen	This class implements random variate generators for the Fisher F distribution with n and m degrees of freedom, where n and m are positive integers.
FoldedNormalGen	This class implements methods for generating random variates from the folded normal distribution with parameters μ >= 0 and σ > 0.
FrechetGen	This class implements methods for generating random variates from the Fréchet distribution, with location parameter δ, scale parameter β > 0, and shape parameter α > 0, where we use the notation z = (x - δ)/β.
GammaAcceptanceRejectionGen	This class implements gamma random variate generators using a method that combines acceptance-rejection with acceptance-complement.
GammaGen	This class implements random variate generators for the gamma distribution.
GammaRejectionLoglogisticGen	This class implements gamma random variate generators using a rejection method with loglogistic envelopes,.
GeometricGen	This class implements a random variate generator for the geometric distribution.
GumbelGen	This class implements methods for generating random variates from the Gumbel distribution.
HalfNormalGen	This class implements methods for generating random variates from the half-normal distribution with parameters μ and σ > 0.
HyperbolicSecantGen	This class implements random variate generators for the hyperbolic secant distribution with location parameter μ and scale parameter σ.
HypergeometricGen	This class implements random variate generators for the hypergeometric distribution.
InverseFromDensityGen	Implements a method for generating random variates by numerical inversion of an arbitrary continuous distribution when only the probability density is known.
InverseGammaGen	This class implements random variate generators for the inverse gamma distribution with shape parameter α > 0 and scale parameter β > 0.
InverseGaussianGen	This class implements random variate generators for the inverse Gaussian distribution with location parameter μ > 0 and scale parameter λ > 0.
InverseGaussianMSHGen	This class implements inverse gaussian random variate generators using the many-to-one transformation method of Michael, Schucany and Haas (MHS).
JohnsonSBGen	This class implements random variate generators for the Johnson SB distribution.
JohnsonSUGen	This class implements random variate generators for the Johnson SU distribution.
KernelDensityGen	This class implements random variate generators for distributions obtained via kernel density estimation methods from a set of n individual observations x1,..., xn.
KernelDensityVarCorrectGen	This class is a variant of KernelDensityGen, but with a rescaling of the empirical distribution so that the variance of the density used to generate the random variates is equal to the empirical variance, as suggested by Silverman.
LogarithmicGen	This class implements random variate generators for the (discrete) logarithmic distribution.
LogisticGen	This class implements random variate generators for the logistic distribution.
LoglogisticGen	This class implements random variate generators for the log-logistic distribution with shape parameter α > 0 and scale parameter β > 0.
LognormalGen	This class implements methods for generating random variates from the lognormal distribution.
LognormalSpecialGen	Implements methods for generating random variates from the lognormal distribution using an arbitrary normal random variate generator.
NakagamiGen	This class implements random variate generators for the Nakagami distribution.
NegativeBinomialGen	This class implements random variate generators having the negative binomial distribution.
NormalACRGen	This class implements normal random variate generators using the acceptance-complement ratio method.
NormalBoxMullerGen	This class implements normal random variate generators using the Box-Muller method.
NormalGen	This class implements methods for generating random variates from the normal distribution N(μ, σ).
NormalInverseGaussianGen	This class implements random variate generators for the normal inverse gaussian (NIG) distribution.
NormalInverseGaussianIGGen	.
NormalKindermannRamageGen	This class implements normal random variate generators using the Kindermann-Ramage method.
NormalPolarGen	This class implements normal random variate generators using the polar method with rejection.
ParetoGen	This class implements random variate generators for one of the Pareto distributions, with parameters α > 0 and β > 0.
PascalConvolutionGen	Implements Pascal random variate generators by the convolution method.
PascalGen	Implements Pascal random variate generators, which is a special case of the negative binomial generator with parameter γ equal to a positive integer.
Pearson5Gen	THIS CLASS HAS BEEN RENAMED InverseGammaGen.
Pearson6Gen	This class implements random variate generators for the Pearson type VI distribution with shape parameters α1 > 0 and α2 > 0, and scale parameter β > 0.
PoissonGen	This class implements random variate generators having the Poisson distribution.
PoissonTIACGen	This class implements random variate generators having the Poisson distribution (see PoissonGen).
PowerGen	This class implements random variate generators for the power distribution with shape parameter c > 0, over the interval [a, b].
RandomVariateGen	This is the base class for all random variate generators over the real line.
RandomVariateGenInt	This is the base class for all generators of discrete random variates over the set of integers.
RandomVariateGenWithCache	This class represents a random variate generator whose values are cached for more efficiency when using common random numbers.
RayleighGen	This class implements random variate generators for the Rayleigh distribution.
StudentGen	This class implements methods for generating random variates from the Student distribution with n > 0 degrees of freedom.
StudentPolarGen	This class implements Student random variate generators using the polar method of.
TriangularGen	This class implements random variate generators for the triangular distribution.
UniformGen	This class implements random variate generators for the (continuous) uniform distribution over the interval (a, b), where a and b are real numbers with a < b.
UniformIntGen	This class implements a random variate generator for the uniform distribution over integers, over the interval [i, j].
UnuranContinuous	This class permits one to create continuous univariate distribution using UNURAN via its string API.
UnuranDiscreteInt	This class permits one to create a discrete univariate distribution using UNURAN via its string API.
UnuranEmpirical	This class permits one to create generators for empirical and quasi-empirical univariate distributions using UNURAN via its string interface.
WeibullGen	This class implements random variate generators for the Weibull distribution.

Exception Summary

Exception	Description
UnuranException	This type of unchecked exception is thrown when an error occurs inside the UNURAN package.