rmvnorm: Multivariate normal simulation.

In dcgerard/tensr: Covariance Inference and Decompositions for Tensor Datasets

Multivariate normal simulation.

Description

Simulate a multivariate normal random matrix.

Usage

rmvnorm(n, mu, Sigma, Sigma.chol = chol(Sigma))

Arguments

n	number of mvnormal vectors to simulate.
mu	mean vector.
Sigma	covariance matrix.
Sigma.chol	Cholesky decomposition of Sigma.

Details

This function simulates multivariate normal random vectors.

Author(s)

Peter Hoff.

Examples

# Simulate several matrices and compute the mean.
Y <- tensr:::rmvnorm(100, c(1, 2, 3), matrix(c(3, 0, 1, 0, 1, -1, 1, -1, 2), 3, 3))
colMeans(Y)
cov(Y)

dcgerard/tensr documentation built on Oct. 4, 2022, 5:58 p.m.