Random matrices simulation from the matrix normal distribution {MN}

Random matrices simulation from the matrix normal distribution

Description

Random matrices simulation from the matrix normal distribution.

Usage

rmn(k, M, U, V)

Arguments

k

The sample size, the number of matrices to simulate.

M

The mean matrix of the distribution, a numerical matrix of dimensions n \times p.

U

The covariance matrix associated with the rows, a numerical matrix of dimensions n \times n.

V

The covariance matrix associated with the columns, a numerical matrix of dimensions p \times p.

Value

A list with k elements, k matrices of dimension n \ times p each. These are the random matrices drawn from a matrix normal distribution.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

https://en.wikipedia.org/wiki/Matrix_normal_distribution#Definition

See Also

dmn, mn.mle, ddplot

Examples

M <- as.matrix(iris[1:8, 1:4])
U <- cov( matrix( rnorm(100 * 8), ncol = 8 ) )
V <- cov( iris[1:50, 1:4] )
X <- rmn(10, M, U, V)