rigaussian: Simulating from inversse Gaussian random variable.

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Simulating from inversse Gaussian random variable.

Description

Using method of Michael and Schucany (1976), we can generate from inversse Gaussian random variable. The density function of an inversse Gaussian distribution is given by

f_W(w\vert{\bold{\theta}}) =\sqrt{\frac{\beta}{2 \pi w^3}}\exp\biggl\{-\frac{\beta(w - \alpha)^2}{2\alpha^2 w}\biggr\},

where w>0 and {\bold{\theta}}=(\alpha, \beta)^{\top}. Herein \alpha>0 is the mean and \beta> 0 are the first (mean) and second (shape) parameter of this family, respectively.

Usage

rigaussian(n, alpha, beta)

Arguments

n	size of required samples.
alpha	tail mean parameter.
beta	shape parameter.

Value

simulated realizations of size n from inversse Gaussian random variable.

Author(s)

Mahdi Teimouri

References

J. R. Michael and Schucany, (1976). Generating Random Variates Using Transformations with Multiple Roots, The American Statistician, 30(2), 88-90, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00031305.1976.10479147")}.

Examples

    n <- 100
alpha <- 4
 beta <- 2
rigaussian(n, alpha, beta)

mixbox documentation built on May 29, 2024, 3:58 a.m.