R: Sample a covariance Matrix from the Posterior Inverse Wishart...

cvPost {RxODE}

R Documentation

Sample a covariance Matrix from the Posterior Inverse Wishart distribution.

Description

Note this Inverse wishart rescaled to match the original scale of the covariance matrix.

Usage

cvPost(nu, omega, n = 1L, omegaIsChol = FALSE, returnChol = FALSE)

Arguments

`nu`	Degrees of Freedom (Number of Observations) for covariance matrix simulation.
`omega`	Estimate of Covariance matrix.
`n`	Number of Matrices to sample. By default this is 1.
`omegaIsChol`	is an indicator of if the omega matrix is in the Cholesky decomposition.
`returnChol`	Return the Cholesky decomposition of the covariance matrix sample.

Details

If your covariance matrix is a 1x1 matrix, this uses an scaled inverse chi-squared which is equivalent to the Inverse Wishart distribution in the uni-directional case.

Value

a matrix (n=1) or a list of matrices (n > 1)

Author(s)

Matthew L.Fidler & Wenping Wang

Examples


## Sample a single covariance.
draw1 <- cvPost(3, matrix(c(1,.3,.3,1),2,2))

## Sample 3 covariances
set.seed(42)
draw3 <- cvPost(3, matrix(c(1,.3,.3,1),2,2), n=3)

## Sample 3 covariances, but return the cholesky decomposition
set.seed(42)
draw3c <- cvPost(3, matrix(c(1,.3,.3,1),2,2), n=3, returnChol=TRUE)

[Package RxODE version 0.9.2-0 Index]