R: Gibbs sampling for a robust regression model

robustt {LearnBayes} | R Documentation

## Gibbs sampling for a robust regression model

### Description

Implements Gibbs sampling for a robust t sampling model with location mu, scale sigma, and degrees of freedom v

### Usage

    robustt(y,v,m)

### Arguments

`y` | vector of data values
`v` | degrees of freedom for t model
`m` | the number of cycles of the Gibbs sampler

### Value

`mu` | vector of simulated values of mu
`s2` | vector of simulated values of sigma2
`lam` | matrix of simulated draws of lambda, where each row corresponds to a single draw

### Author(s)

Jim Albert

### Examples

    data=c(-67,-48,6,8,14,16,23,24,28,29,41,49,67,60,75)
    fit=robustt(data,4,1000)

[Package LearnBayes version 2.15 Index]