# rmatrixCHIIkind2: Sampler of the matrix variate type II confluent... In matrixsampling: Simulations of Matrix Variate Distributions

## Description

Samples the matrix variate type II confluent hypergeometric kind two distribution.

## Usage

 `1` ```rmatrixCHIIkind2(n, nu, alpha, beta, theta = 1, p) ```

## Arguments

 `n` sample size, a positive integer `nu` shape parameter, a positive number; if `nu < (p-1)/2`, then `nu` must be a half integer `alpha, beta` shape parameters; `alpha > (p-1)/2`, `beta < nu + 1` `theta` scale parameter, a positive number `p` dimension (order of the sampled matrices), an integer greater than or equal to one

## Value

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

## References

A. K. Gupta & D. K. Nagar. Matrix Variate Distributions. Chapman & Hall/CRC, Boca Raton (2000).

## Examples

 ```1 2 3 4 5 6``` ```nu <- 5; alpha <- 13; beta <- 4; theta <- 2; p <- 2 sims <- rmatrixCHIIkind2(50000, nu, alpha, beta, theta, p) # simulations of the trace trsims <- apply(sims, 3, function(X) sum(diag(X))) mean(trsims) p * theta * nu * (nu+(p+1)/2-beta) / (alpha+nu+(p+1)/2-beta) ```

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