rmvnorm: Generate data from the multivariate Normal distribution

In BDgraph: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

Generate data from the multivariate Normal distribution

Description

Random generation function from the multivariate Normal distribution with mean equal to mean and covariance matrix sigma.

Usage

 
    rmvnorm( n = 10, mean = rep( 0, length = ncol( sigma ) ), 
             sigma = diag( length( mean ) ) ) 

Arguments

n	Number of observations.
mean	Mean vector, default is rep( 0, length = ncol( sigma ) ).
sigma	positive definite covariance matrix, default is diag( length( mean ) ) .

Value

A numeric matrix with rows equal to n and columns equal to length( mean ).

Author(s)

Reza Mohammadi [e-mail]

See Also

bdgraph.sim, rwish, rgwish

Examples

mean  <- c( 5, 20 )       
sigma <- matrix( c( 4, 2,
                    2, 5 ), 2, 2 )  # covariance matrix

sample <- rmvnorm( n = 500, mean = mean, sigma = sigma )
plot( sample )

BDgraph documentation built on Sept. 11, 2024, 5:30 p.m.