sim_matgaussian {bvhar} | R Documentation |
Generate Matrix Normal Random Matrix
Description
This function samples one matrix gaussian matrix.
Usage
sim_matgaussian(mat_mean, mat_scale_u, mat_scale_v)
Arguments
mat_mean |
Mean matrix |
mat_scale_u |
First scale matrix |
mat_scale_v |
Second scale matrix |
Details
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
andV = 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
.
Value
One n x k matrix following MN distribution.
[Package bvhar version 2.0.1 Index]