stable_rnd: Skew stable distribution random sample generation.

In libstableR: Fast and Accurate Evaluation, Random Number Generation and Parameter Estimation of Skew Stable Distributions

Description

stable_rnd(N, pars) generates N random samples of a skew stable distribuiton with parameters pars = c(alpha, beta, sigma, mu) using the Chambers, Mallows, and Stuck (1976) method.

Usage

stable_rnd(N, pars, parametrization = 0L)

Arguments

N	Number of values to generate.
pars	Vector with an initial estimation of the parameters. pars_init = c(alpha, beta, sigma, mu), where alpha: shape / stability parameter, with 0 < alpha <= 2. beta: skewness parameter, with -1 <= beta <= 1. sigma: scale parameter, with 0 < sigma. mu: location parameter, with mu real.
parametrization	Parametrization used for the skew stable distribution, as defined by JP Nolan (1997). By default, parametrization = 0.

Value

A numeric vector.

Author(s)

Javier Royuela del Val, Federico Simmross Wattenberg and Carlos Alberola López

Maintainer: Javier Royuela del Val [e-mail]

References

Chambers JM, Mallows CL, Stuck BW (1976). A Method for Simulating Stable Random Variables. Journal of the American Statistical Association, 71(354), 340-344. doi:10.1080/01621459.1976.10480344.

Examples

N <- 1000
pars <- c(1.25, 0.95, 1.0, 0.0)
rnd <- stable_rnd(N, pars)

hist(rnd)

libstableR documentation built on May 2, 2019, 8:49 a.m.