Package umontreal.iro.lecuyer.randvar

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



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