# rGenWish: Simulate realizations from the Generalized Wishart... In rwc: Random Walk Covariance Models

## Description

Simulates Wishart random variables, then computes the induced distance of the simulated Wishart random variables. The result is a random matrix distributed as a Generalized Wishart random variable.

## Usage

 `1` ```rGenWish(Sigma, df) ```

## Arguments

 `Sigma` The covariance parameter of the Generalized Wishart. `df` An integer specifying the degrees of freedom.

## Value

A matrix of dimension equal to the dimension of Sigma.

Ephraim M. Hanks

## References

McCullagh 2009. Marginal likelihood for distance matrices. Statistica Sinica 19: 631-649.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```ras=raster(nrow=30,ncol=30) extent(ras) <- c(0,30,0,30) values(ras) <- 1 int=ras cov.ras=ras ## get precision matrix of entire graph B.int=get.TL(int) Q.int=get.Q(B.int,1) ## get precision at a few nodes Phi=get.Phi(Q.int,obs.idx=1:20) S=ginv(as.matrix(Phi)) ## simulate distance matrix Dsim=rGenWish(df=20,Sigma=S) image(Dsim) ## calculate log-likelihood ll=dGenWish(Dsim,S,df=20,log=TRUE) ll ```

rwc documentation built on May 2, 2019, 3:34 p.m.