rmvlogis {mvpd} | R Documentation |
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))
## Not run:
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)
## End(Not run)
[Package mvpd version 0.0.5 Index]