cgeneric_Wishart: Build an 'inla.cgeneric' to implement the Wishart prior for a...
In graphpcor: Models for Correlation Matrices Based on Graphs

cgeneric_Wishart

R Documentation

Build an `inla.cgeneric` to implement the Wishart prior for a precision matrix.

Description

Build an inla.cgeneric to implement the Wishart prior for a precision matrix.

Usage

cgeneric_Wishart(
  n,
  dof,
  R,
  debug = FALSE,
  useINLAprecomp = TRUE,
  libpath = NULL
)

Arguments

`n`	the size of the precision matrix
`dof`	degrees of freedom model parameter
`R`	lower triangle of the scale matrix parameter
`debug`	integer, default is zero, indicating the verbose level. Will be used as logical by INLA.
`useINLAprecomp`	logical, default is TRUE, indicating if it is to be used the shared object pre-compiled by INLA. This is not considered if 'libpath' is provided.
`libpath`	string, default is NULL, with the path to the shared object.

Details

For a random p\times p precision matrix Q, given the parameters d and R, respectively scalar degree of freedom and the inverse scale p\times p matrix the Wishart density is

|Q|^{(d-p-1)/2}\textrm{e}^{-tr(RQ)/2}|R|^{p/2}2^{-dp/2}\Gamma_p(n/2)^{-1}