MixGHD (version 2.3.7)

rMSGHD: Pseudo random number generation from a mulitple-scaled generalized hyperbolic distribution (MSGHD).

Description

Generate n pseudo random numbers from a p dimensional mulitple-scaled generalized hyperbolic distribution.

Usage

rMSGHD(n,p, mu=rep(0,p),alpha=rep(0,p),sigma=diag(p),omegav=rep(1,p),lambdav=rep(0.5,p))

Arguments

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

omegav

(optional) the p dimensional concentration parameter omega

lambdav

(optional) the p dimensional index parameter lambda

Value

A n times p matrix of numbers psudo randomly generated from a generilzed hyperbolic distribution

Details

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.

References

C. Tortora, B.C. Franczak, R.P. Browne, and P.D. McNicholas (2019). A Mixture of Coalesced Generalized Hyperbolic Distributions. Journal of Classification (to appear).

Examples

# NOT RUN {
data=rMSGHD(300,2,alpha=c(2,-2),omegav=c(2,2))

plot(data)
# }