urgig {Runuran}R Documentation

UNU.RAN Generalized Inverse Gaussian Distribution variate generator

Description

UNU.RAN random variate generator for the Generalized Inverse Gaussian Distribution with parameters lambda and omega. It also allows sampling from the truncated distribution.

[Distribution] – Sampling Function: GIG (generalized inverse Gaussian).

Usage

urgig(n, lambda, omega, lb=1.e-12, ub=Inf)

Arguments

n size of required sample.
lambda (strictly positive) shape parameter.
omega (strictly positive) shape parameter.
lb lower bound of (truncated) distribution
ub upper bound of (truncated) distribution

Details

The Generalized Inverse Gaussian distribution with parameters lambda =a and omega =b has a density proportional to

f(x) ~ x^(a-1) exp(-(b/2)(x+1/x))

for x >= 0, a > 0 and b > 0.

The generation algorithm uses transformed density rejection ‘TDR’. The parameters lb and ub can be used to generate variates from the distribution truncated to the interval (lb,ub).

The generation algorithm works for λ >= 1 and omega>0 and for λ>0 and omega >= 0.5.

Note

This function is wrapper for the UNU.RAN class in R.

Author(s)

Josef Leydold and Wolfgang H"ormann unuran@statmath.wu-wien.ac.at.

References

W. H"ormann, J. Leydold, and G. Derflinger (2004): Automatic Nonuniform Random Variate Generation. Springer-Verlag, Berlin Heidelberg.

N.L. Johnson, S. Kotz, and N. Balakrishnan (1994): Continuous Univariate Distributions, Volume 1. 2nd edition, John Wiley & Sons, Inc., New York. Chap.15, p.284.

See Also

runif and .Random.seed about random number generation and unuran for the UNU.RAN class.

Examples

## Create a sample of size 1000
x <- urgig(n=1000,lambda=2,omega=3)

[Package Runuran version 0.9.0 Index]