mvtnorm: Mvnorm – R documentation

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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 = rep(0, p), sigma = diag(p), log = FALSE, checkSymmetry = TRUE)
rmvnorm(n, mean = rep(0, nrow(sigma)), sigma = diag(length(mean)),
        method=c("eigen", "svd", "chol"), pre0.9_9994 = FALSE, checkSymmetry = TRUE)

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`	string specifying the 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"`). The Cholesky is typically fastest, not by much though.
`pre0.9_9994`	logical; if `FALSE`, the output produced in mvtnorm versions up to 0.9-9993 is reproduced. In 0.9-9994, the output is organized such that `rmvnorm(10,...)` has the same first ten rows as `rmvnorm(100, ...)` when called with the same seed.
`checkSymmetry`	logical; if `FALSE`, skip checking whether the covariance matrix is symmetric or not. This will speed up the computation but may cause unexpected outputs when ill-behaved `sigma` is provided. The default value is `TRUE`.

Author(s)

Friedrich Leisch and Fabian Scheipl

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)

mvtnorm

Multivariate Normal and t Distributions

v1.1-1

GPL-2

Authors

Alan Genz [aut], Frank Bretz [aut], Tetsuhisa Miwa [aut], Xuefei Mi [aut], Friedrich Leisch [ctb], Fabian Scheipl [ctb], Bjoern Bornkamp [ctb] (<https://orcid.org/0000-0002-6294-8185>), Martin Maechler [ctb], Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)

Initial release

2020-06-09