Pseudo random number generation from a generalized hyperbolic distribution (GHD).
Generate n pseudo random numbers from a p dimensional generalized hyperbolic distribution.
rGHD(n,p, mu=rep(0,p),alpha=rep(0,p),sigma=diag(p),omega=1,lambda=0.5)
n |
number of observations. |
p |
number of variables. |
mu |
(optional) the p dimensional mean |
alpha |
(optional) the p dimensional skewness parameter alpha |
sigma |
(optional) the p x p dimensional scale matrix |
omega |
(optional) the unidimensional concentration parameter omega |
lambda |
(optional) the unidimensional index parameter lambda |
The default values are: 0 for the mean and the skweness parameter alpha, diag(p) for sigma, 1 for omega, and 0.5 for lambda.
A n times p matrix of numbers psudo randomly generated from a generilzed hyperbolic distribution
Cristina Tortora, Aisha ElSherbiny, Ryan P. Browne, Brian C. Franczak, and Paul D. McNicholas. Maintainer: Cristina Tortora <cristina.tortora@sjsu.edu>
R.P. Browne, and P.D. McNicholas (2015). A Mixture of Generalized Hyperbolic Distributions. Canadian Journal of Statistics, 43.2 176-198
data=rGHD(300,2,alpha=c(2,-2)) plot(data)
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