robustt: Gibbs sampling for a robust regression model

In bayesball/LearnBayes: Learning Bayesian Inference

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)

bayesball/LearnBayes documentation built on May 11, 2019, 9:21 p.m.