rsmvnorm {SimCorMultRes}

Simulating Continuous Random Vectors from a Multivariate Normal Distribution

Description

Utility function to simulate continuous random vectors from a multivariate normal distribution such that all marginal distributions are univariate standard normal.

Usage

rsmvnorm(R = R, cor.matrix = cor.matrix)

Arguments

R

integer indicating the sample size.

cor.matrix

matrix indicating the correlation matrix of the multivariate normal distribution.

Details

Checks are made to ensure that cor.matrix is a positive definite correlation matrix. The positive definiteness of cor.matrix is assessed via eigenvalues.

Value

Returns R random vectors of size ncol(cor.matrix).

Author(s)

Anestis Touloumis

Examples

## Simulating 10000 bivariate random vectors with correlation parameter
## equal to 0.4.
set.seed(1)
sample_size <- 10000
correlation_matrix <- toeplitz(c(1, 0.4))
simulated_normal_responses <- rsmvnorm(R = sample_size,
  cor.matrix = correlation_matrix)
colMeans(simulated_normal_responses)
apply(simulated_normal_responses, 2, sd)
cor(simulated_normal_responses)