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Generate Normal-IW Random Family

Source: R/generate-process.R
sim_mniw.Rd

This function samples normal inverse-wishart matrices.

Usage

sim_mniw(num_sim, mat_mean, mat_scale_u, mat_scale, shape, u_prec = FALSE)

Arguments

num_sim

Number to generate

mat_mean

Mean matrix of MN

mat_scale_u

First scale matrix of MN

mat_scale

Scale matrix of IW

shape

Shape of IW

u_prec

If TRUE, use mat_scale_u as its inverse. By default, FALSE.

Details

Consider \((Y_i, \Sigma_i) \sim MIW(M, U, \Psi, \nu)\).

  1. Generate upper triangular factor of \(\Sigma_i = C_i C_i^T\) in the upper triangular Bartlett decomposition.

  2. Standard normal generation: n x k matrix \(Z_i = [z_{ij} \sim N(0, 1)]\) in row-wise direction.

  3. Lower triangular Cholesky decomposition: \(U = P P^T\)

  4. \(A_i = M + P Z_i C_i^T\)