This function samples one matrix gaussian matrix.
sim_matgaussian(mat_mean, mat_scale_u, mat_scale_v, u_prec)One n x k matrix following MN distribution.
Mean matrix
First scale matrix
Second scale matrix
If TRUE, use mat_scale_u as its inverse.
Consider n x k matrix \(Y_1, \ldots, Y_n \sim MN(M, U, V)\) where M is n x k, U is n x n, and V is k x k.
Lower triangular Cholesky decomposition: \(U = P P^T\) and \(V = L L^T\)
Standard normal generation: s x m matrix \(Z_i = [z_{ij} \sim N(0, 1)]\) in row-wise direction.
\(Y_i = M + P Z_i L^T\)
This function only generates one matrix, i.e. \(Y_1\).