MatrixT: The Matrix-t distribution.

In mniw: The Matrix-Normal Inverse-Wishart Distribution

The Matrix-t distribution.

Description

Density and sampling for the Matrix-t distribution.

Usage

dMT(X, Lambda, SigmaR, SigmaC, nu, log = FALSE)

rMT(n, Lambda, SigmaR, SigmaC, nu)

Arguments

X	Argument to the density function. Either a p x q matrix or a p x q x n array.
Lambda	Mean parameter Either a p x q matrix or a p x q x n array.
SigmaR	Between-row covariance matrix. Either a p x p matrix or a p x p x n array.
SigmaC	Between-column covariance matrix Either a q x q matrix or a q x q x n array.
nu	Degrees-of-freedom parameter. A scalar or vector of length n.
log	Logical; whether or not to compute the log-density.
n	Integer number of random samples to generate.

Details

The Matrix-T distribution X ~ Matrix-T(Λ, Σ, Ψ, ν) on a random matrix X_(p x q) is the marginal distribution of X in (X, V) ~ MNIW(Λ, Σ, Ψ, ν), where the Matrix-Normal Inverse-Wishart (MNIW) distribution is defined in mniw.

Value

A vector length n for density evaluation, or an array of size p x q x n for random sampling.

mniw documentation built on Aug. 22, 2022, 5:05 p.m.