mvpd (version 0.0.5)

rmvlogis: Multivariate Logistic Random Variables

Description

Computes random vectors of the multivariate symmetric logistic distribution for arbitrary correlation matrices using the asymptotic Kolmogorov distribution -- see references.

Usage

rmvlogis(n, Q = NULL, delta = rep(0, d), BIG = 500)

Arguments

n

number of observations

Q

semi-positive definite

delta

location vector.

BIG

the number of exponential to add for asymptotic Kolomogrov

References

Scale Mixtures of Normal Distributions Author(s): D. F. Andrews and C. L. Mallows Source: Journal of the Royal Statistical Society. Series B (Methodological), Vol. 36, No. 1 (1974), pp. 99-102 Published by: Wiley for the Royal Statistical Society Stable URL: http://www.jstor.org/stable/2984774

Examples

rmvlogis(10, Q=diag(5))

if (FALSE) {
QMAT <- matrix(c(1,0,0,1),nrow=2)
draw_NNMD  <- NonNorMvtDist::rmvlogis(2e3, parm1=rep(0,2), parm2=rep(1,2))
draw_mvpd  <-          mvpd::rmvlogis(2e3,     Q=QMAT)

mean(draw_NNMD[,1]   < -1 & draw_NNMD[,2]   < 3)
mean(draw_mvpd[,1] < -1 & draw_mvpd[,2] < 3)

plogis(-1)
mean(draw_NNMD[,1] < -1)
mean(draw_mvpd[,1] < -1)

plogis(3)
mean(draw_NNMD[,2] < 3)
mean(draw_mvpd[,2] < 3)
 
rangex <- range(c(draw_mvpd[,1],draw_NNMD[,1]))
rangey <- range(c(draw_mvpd[,2],draw_NNMD[,2]))

par(mfrow=c(3,2), pty="s", mai=c(.5,.1,.1,.1))
plot(draw_NNMD, xlim=rangex, ylim=rangey); abline(h=0,v=0)
plot(draw_mvpd   , xlim=rangex, ylim=rangey); abline(h=0,v=0)

hist(draw_NNMD[,1]  , breaks = 100,  xlim=rangex, probability=TRUE, ylim=c(0,.40))
curve(dlogis(x), add=TRUE, col="blue",lwd=2)
hist(draw_mvpd[,1], breaks = 100,  xlim=rangex, probability=TRUE, ylim=c(0,.40))
curve(dlogis(x), add=TRUE, col="blue",lwd=2)
hist(draw_NNMD[,2]  , breaks = 100,  xlim=rangex, probability=TRUE, ylim=c(0,.40))
curve(dlogis(x), add=TRUE, col="blue",lwd=2)
hist(draw_mvpd[,2], breaks = 100,  xlim=rangex, probability=TRUE, ylim=c(0,.40))
curve(dlogis(x), add=TRUE, col="blue",lwd=2)
}