mvtnorm (version 0.9-9992)

Mvnorm: Multivariate Normal Density and Random Deviates

Description

These functions provide the density function and a random number generator for the multivariate normal distribution with mean equal to mean and covariance matrix sigma.

Usage

dmvnorm(x, mean, sigma, log=FALSE)
rmvnorm(n, mean = rep(0, nrow(sigma)), sigma = diag(length(mean)),
        method=c("eigen", "svd", "chol"))

Arguments

x

Vector or matrix of quantiles. If x is a matrix, each row is taken to be a quantile.

n

Number of observations.

mean

Mean vector, default is rep(0, length = ncol(x)).

sigma

Covariance matrix, default is diag(ncol(x)).

log

Logical; if TRUE, densities d are given as log(d).

method

Matrix decomposition used to determine the matrix root of sigma, possible methods are eigenvalue decomposition ("eigen", default), singular value decomposition ("svd"), and Cholesky decomposition ("chol"

See Also

pmvnorm, rnorm, qmvnorm

Examples

dmvnorm(x=c(0,0))
dmvnorm(x=c(0,0), mean=c(1,1))

sigma <- matrix(c(4,2,2,3), ncol=2)
x <- rmvnorm(n=500, mean=c(1,2), sigma=sigma)
colMeans(x)
var(x)

x <- rmvnorm(n=500, mean=c(1,2), sigma=sigma, method="chol")
colMeans(x)
var(x)

plot(x)