[randvar] Generators for Continuous Distributions

Classes
class	BetaGen
	This class implements random variate generators with the beta distribution with shape parameters \(\alpha> 0\) and \(\beta> 0\), over the interval \((a,b)\), where \(a < b\). More...
class	BetaRejectionLoglogisticGen
	Implements Beta random variate generators using the rejection method with log-logistic envelopes from [34] . More...
class	BetaStratifiedRejectionGen
	This class implements Beta random variate generators using the stratified rejection/patchwork rejection method from [210], [223] . More...
class	BetaSymmetricalBestGen
	This class implements symmetrical beta random variate generators using Devroye’s one-liner method. More...
class	BetaSymmetricalGen
	This class implements random variate generators with the symmetrical beta distribution with shape parameters \(\alpha= \beta\), over the interval \((0,1)\). More...
class	BetaSymmetricalPolarGen
	This class implements symmetrical beta random variate generators using Ulrich’s polar method [232] . More...
class	CauchyGen
	This class implements random variate generators for the Cauchy distribution. More...
class	ChiGen
	This class implements random variate generators for the chi distribution. More...
class	ChiRatioOfUniformsGen
	This class implements Chi random variate generators using the ratio of uniforms method with shift. More...
class	ChiSquareGen
	This class implements random variate generators with the chi square distribution with \(n>0\) degrees of freedom. More...
class	ChiSquareNoncentralGamGen
	This class implements noncentral chi square random variate generators using the additive property of the noncentral chi square distribution [115] . More...
class	ChiSquareNoncentralGen
	This class implements random variate generators for the noncentral chi square distribution with \(\nu> 0\) degrees of freedom and noncentrality parameter \(\lambda> 0\). More...
class	ChiSquareNoncentralPoisGen
	This class implements noncentral chi square random variate generators using Poisson and central chi square generators. More...
class	ConstantGen
	This class implements a random variate generator that returns a constant value. More...
class	ErlangConvolutionGen
	This class implements Erlang random variate generators using the convolution method. More...
class	ErlangGen
	This class implements random variate generators for the Erlang distribution with parameters \(k > 0\) and \(\lambda> 0\). More...
class	ExponentialGen
	This class implements random variate generators for the exponential distribution. More...
class	ExponentialInverseFromDensityGen
	This class implements exponential random variate generators using numerical inversion of the exponential density as described in [44] . More...
class	ExtremeValueGen
	This class has been replaced by GumbelGen . More...
class	FatigueLifeGen
	This class implements random variate generators for the fatigue life distribution [20]  with location parameter \(\mu\), scale parameter \(\beta\) and shape parameter \(\gamma\). More...
class	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. More...
class	FNoncentralGen
	This class implements random variate generators for the noncentral F-distribution. More...
class	FoldedNormalGen
	This class implements methods for generating random variates from the folded normal distribution with parameters \(\mu\ge0\) and \(\sigma> 0\). More...
class	FrechetGen
	This class implements methods for generating random variates from the Fréchet distribution, with location parameter \(\delta\), scale parameter \(\beta> 0\), and shape parameter \(\alpha> 0\), where we use the notation \(z = (x-\delta)/\beta\). More...
class	GammaAcceptanceRejectionGen
	This class implements gamma random variate generators using a method that combines acceptance-rejection with acceptance-complement, and proposed in [2], [4] . More...
class	GammaGen
	This class implements random variate generators for the gamma distribution. More...
class	GammaRejectionLoglogisticGen
	This class implements gamma random variate generators using a rejection method with loglogistic envelopes, from [33] . More...
class	GumbelGen
	This class implements methods for generating random variates from the Gumbel distribution. More...
class	HalfNormalGen
	This class implements methods for generating random variates from the half-normal distribution with parameters \(\mu\) and \(\sigma> 0\). More...
class	HyperbolicSecantGen
	This class implements random variate generators for the hyperbolic secant distribution with location parameter \(\mu\) and scale parameter \(\sigma\). More...
class	HypoExponentialGen
	This class implements random variate generators for the hypoexponential distribution (see classes umontreal.ssj.probdist.HypoExponentialDist and umontreal.ssj.probdist.HypoExponentialDistQuick in package probdist for the definition). More...
class	InverseGammaGen
	This class implements random variate generators for the inverse gamma distribution with shape parameter \(\alpha> 0\) and scale parameter \(\beta> 0\). More...
class	InverseGaussianGen
	This class implements random variate generators for the inverse Gaussian distribution with location parameter \(\mu> 0\) and scale parameter \(\lambda> 0\). More...
class	InverseGaussianMSHGen
	This class implements inverse gaussian random variate generators using the many-to-one transformation method of Michael, Schucany and Haas (MHS) [180], [48] . More...
class	JohnsonSBGen
	This class implements random variate generators for the Johnson \(S_B\) distribution. More...
class	JohnsonSLGen
	This class implements random variate generators for the Johnson \(S_L\) distribution. More...
class	JohnsonSUGen
	This class implements random variate generators for the Johnson \(S_U\) distribution. More...
class	JohnsonSystemG
	This class contains common parameters and methods for the random variate generators associated with the Johnson system of distributions [101], [99] . More...
class	KernelDensityGen
	This class implements random variate generators for distributions obtained via kernel density estimation methods from a set of \(n\) individual observations \(x_1,…,x_n\) [45], [46], [89], [90], [215] . More...
class	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 [215] . More...
class	LaplaceGen
	This class implements methods for generating random variates from the Laplace distribution. More...
class	LogisticGen
	This class implements random variate generators for the logistic distribution. More...
class	LoglogisticGen
	This class implements random variate generators for the log-logistic distribution with shape parameter \(\alpha> 0\) and scale parameter \(\beta> 0\). More...
class	LognormalGen
	This class implements methods for generating random variates from the lognormal distribution. More...
class	LognormalSpecialGen
	Implements methods for generating random variates from the lognormal distribution using an arbitrary normal random variate generator. More...
class	MixtureGen
	This class implements random variate generators for a mixture distribution. More...
class	NakagamiGen
	This class implements random variate generators for the Nakagami distribution. More...
class	NormalACRGen
	This class implements normal random variate generators using the acceptance-complement ratio method [87] . More...
class	NormalBoxMullerGen
	This class implements normal random variate generators using the Box-Muller method from [23] . More...
class	NormalGen
	This class implements methods for generating random variates from the normal distribution \(N(\mu, \sigma)\). More...
class	NormalInverseFromDensityGen
	This class implements normal random variate generators using numerical inversion of the normal density as described in [44] . More...
class	NormalInverseGaussianGen
	This class implements random variate generators for the normal inverse gaussian ( \(\mathcal{NIG}\)) distribution. More...
class	NormalInverseGaussianIGGen
	This class implements a normal inverse gaussian ( \({NIG}\)) random variate generator by using a normal generator ( \(N\)) and an inverse gaussian generator ( \(IG\)), as described in the following [239], [103] . More...
class	NormalKindermannRamageGen
	This class implements normal random variate generators using the Kindermann-Ramage method [106] . More...
class	NormalPolarGen
	This class implements normal random variate generators using the polar method with rejection [176] . More...
class	ParetoGen
	This class implements random variate generators for one of the Pareto distributions, with parameters \(\alpha>0\) and \(\beta>0\). More...
class	Pearson5Gen
	THIS CLASS HAS BEEN RENAMED InverseGammaGen . More...
class	Pearson6Gen
	This class implements random variate generators for the Pearson type VI distribution with shape parameters \(\alpha_1 > 0\) and \(\alpha_2 > 0\), and scale parameter \(\beta> 0\). More...
class	PowerGen
	This class implements random variate generators for the power distribution with shape parameter \(c > 0\), over the interval \([a,b]\). More...
class	RayleighGen
	This class implements random variate generators for the Rayleigh distribution. More...
class	StudentGen
	This class implements methods for generating random variates from the Student distribution with \(n>0\) degrees of freedom. More...
class	StudentNoncentralGen
	This class implements random variate generators for the noncentral Student-t distribution with \(n>0\) degrees of freedom and noncentrality parameter \(\delta\). More...
class	StudentPolarGen
	This class implements Student random variate generators using the polar method of [14] . More...
class	TriangularGen
	This class implements random variate generators for the triangular distribution. More...
class	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 \(a < b\). More...
class	WeibullGen
	This class implements random variate generators for the Weibull distribution. More...

Detailed Description