reg.gprior.post: Computes the log posterior of a normal regression model with...
In LearnBayes: Functions for Learning Bayesian Inference

Description Usage Arguments Value Author(s) Examples

Computes the log posterior of (beta, log sigma) for a normal regression model with a g prior with parameters beta0 and c0.

1	reg.gprior.post(theta, dataprior)

`theta`	vector of components of beta and log sigma
`dataprior`	list with components data and prior; data is a list with components y and X, prior is a list with components b0 and c0

value of the log posterior

Jim Albert

data(puffin)
data=list(y=puffin$Nest, X=cbind(1,puffin$Distance))
prior=list(b0=c(0,0), c0=10)
reg.gprior.post(c(20,-.5,1),list(data=data,prior=prior))