MVNorm {DIRECT}  R Documentation 
Functions to compute the density of a multivariate normal distribution and to generate random realizations from such a distribution.
dMVNorm (x, mean, sigma, log = FALSE)
rMVNorm (n, mean = rep(0, nrow(sigma)), sigma = diag(length(mean)),
method=c("eigen", "svd", "chol"))
x 
Vector or matrix of quantiles. If 
n 
Number of realizations. 
mean 
Mean vector, default is 
sigma 
Covariance matrix, default is 
log 
Logical; if 
method 
Matrix decomposition used to determine the matrix root of

rMVNorm
returns a vector of the same length as mean
if n
=1, or a matrix with each row being an independent realization otherwise.
The code for both functions is taken from similar functions written by Friedrich Leisch and Fabian Scheipl in R package mvtnorm
. Audrey Q. Fu modified dMVNorm
to use a different method to compute the matrix determinants.
## Not run:
x < rMVNorm (10, mean=rep(0,3), method="svd")
dMVNorm (x, mean=rep(0,3), log=TRUE)
## End(Not run)