Sample from a matrix-normal distribution

Usage

rmatrixnorm(mu, L_sigma_rows, L_sigma_cols)

Arguments

mu: a matrix of means
L_sigma_rows: the Cholesky-decomposed covariance matrix for the rows
L_sigma_cols: the Cholesky-decomposed covariance matrix for the columns

Value

A single sample from a matrix-normal distribution with mean mu (a matrix), row-wise covariances sigma_rows, and column-wise covariances sigma_cols, where L_sigma_rows and L_sigma_cols are the Cholesky-decomposed covariance matrices

Examples

mu <- matrix(rep(0, 8), nrow = 4)
sd_rows <- rep(1, 4)
sd_cols <- rep(1, 2)
r_rows <- cor_matrix(.25, 4)
r_cols <- cor_matrix(.75, 2)
L_sigma_rows <- chol(cov_matrix(sd_rows, r_rows))
L_sigma_cols <- chol(cov_matrix(sd_cols, r_cols))
rmatrixnorm(mu, L_sigma_rows, L_sigma_cols)
#>            [,1]        [,2]
#> [1,] -1.1382370 -0.82862066
#> [2,] -0.2845322 -0.05698198
#> [3,] -0.4903762 -1.38679481
#> [4,]  0.4629313  0.49554507