R: Computes the log posterior of a normal regression model with...

reg.gprior.post {LearnBayes} | R Documentation

## Computes the log posterior of a normal regression model with a g prior.

### Description

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

### Usage

    reg.gprior.post(theta, dataprior)

### Arguments

`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

value of the log posterior

### Author(s)

Jim Albert

### Examples

    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))

[Package LearnBayes version 2.15 Index]