rmvt {mvgb}R Documentation

Multivariate t Distribution Random Variates

Description

Computes random vectors of the multivariate t distribution distribution for arbitrary correlation matrices using gamma variates not chi/sqrt(nu).

Usage

rmvt(n, df = 30, Q = NULL, delta = rep(0, d))

Arguments

n

number of observations

df

default to 30.

Q

semi-positive definite

delta

location vector.

Value

A n by d matrix containing multivariate t random variates where d=nrow(Q).

References

Genz, A. and Bretz, F. (2002), Methods for the computation of multivariate t-probabilities. Journal of Computational and Graphical Statistics, 11, 950–971.

Examples

## sample usage
rmvt(10, df=4, Q=diag(5))

## compare to rmvt from mvtnorm R-package
draw_mvtnorm <- mvtnorm::rmvt(2e4, sigma=diag(2), df = 35)
draw_mvgb    <-    mvgb::rmvt(2e4,     Q=diag(2), df = 35)

rangex <- range(c(draw_mvgb[,1],draw_mvtnorm[,1]))
rangey <- range(c(draw_mvgb[,2],draw_mvtnorm[,2]))

## https://stackoverflow.com/a/53804499/2727349
opar <- par(mfrow=c(2,2))
plot(draw_mvtnorm, xlim=rangex, ylim=rangey); abline(h=0,v=0)
plot(draw_mvgb   , xlim=rangex, ylim=rangey); abline(h=0,v=0)

hist(draw_mvtnorm, breaks = 100, ylim=c(0,4000), xlim=rangex)
hist(draw_mvgb   , breaks = 100, ylim=c(0,4000), xlim=rangex)
par(opar)


[Package mvgb version 0.0.1 Index]