# rmatrixgamma: Matrix Gamma sampler In matrixsampling: Simulations of Matrix Variate Distributions

## Description

Samples a matrix Gamma distribution.

## Usage

 `1` ```rmatrixgamma(n, nu, theta, Sigma = NULL, p, checkSymmetry = TRUE) ```

## Arguments

 `n` sample size, a positive integer `nu` shape parameter, a positive number; if `nu < (p-1)/2`, where `p` is the dimension (the order of `Sigma`), then `nu` must be a half integer `theta` scale parameter, a positive number `Sigma` scale matrix, a symmetric positive definite matrix, or `NULL` for the identity matrix of order `p` `p` if `Sigma` is `NULL`, this sets `Sigma` to the identity matrix of order `p`; ignored if `Sigma` is not `NULL` `checkSymmetry` logical, whether to check that `Sigma` is a symmetric positive definite matrix

## Details

This is the distribution of θ/2×S where S ~ Wp(2ν,Σ).

## Value

A numeric three-dimensional array; simulations are stacked along the third dimension.

## References

Gupta & al. Properties of Matrix Variate Confluent Hypergeometric Function Distribution. Journal of Probability and Statistics vol. 2016, Article ID 2374907, 12 pages, 2016.

## Examples

 ```1 2 3 4``` ```nu <- 3; theta <- 4; Sigma <- toeplitz(2:1) Gsims <- rmatrixgamma(10000, nu, theta, Sigma) apply(Gsims, c(1,2), mean) # should be nu * theta * Sigma nu * theta * Sigma ```

matrixsampling documentation built on Aug. 25, 2019, 1:03 a.m.