rgig: Random value generation from the Generalized Inverse Gaussian...

In NGBVS: Bayesian Variable Selection for SNP Data using Normal-Gamma

Random value generation from the Generalized Inverse Gaussian Distribution

Description

Random value generation from the Generalized Inverse Gaussian (GIG) Distribution.

Usage

rgig(n = 10, lambda = 1, chi = 1, psi = 1)

Arguments

n	Number of observations.
lambda	A shape and scale and parameter.
chi	Shape parameter. Must be positive.
psi	Scale parameter. Must be positive.

Details

rgig uses the code from the GIG-random number generator from the R package fBasics. I copied the code from the "ghyp" package because it had not longer a maintainer.

Value

A vector with random values from the GIG distrigution.

Author(s)

David Luethi. Minor changes made by Abdulaziz Alenazi [e-mail].

References

The algorithm for simulating generalized inverse gaussian variates is copied from the R package fBasics from Diethelm Wuertz.

Dagpunar, J.S. (1989). An easily implemented generalised inverse Gaussian generator. Communications in Statistics-Computation and Simulation, 18, 703–710.

Raible S. (2000). Levy Processes in Finance: Theory, Numerics and Empirical Facts, PhD Thesis, University of Freiburg, Germany, 161 pages.

Examples

x <- rgig(n = 10, lambda = 1, chi = 1, psi = 1)

NGBVS documentation built on Sept. 16, 2022, 5:06 p.m.