Getting Started Example 1 for PROC MCMC
/****************************************************************/
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: MCMCGS1 */
/* TITLE: Getting Started Example 1 for PROC MCMC */
/* PRODUCT: STAT */
/* SYSTEM: ALL */
/* KEYS: regression analysis */
/* PROCS: MCMC */
/* DATA: */
/* */
/* SUPPORT: Fang Chen */
/* REF: PROC MCMC, GETTING STARTED EXAMPLE 1 */
/* MISC: */
/****************************************************************/
title 'Simple Linear Regression';
data Class;
input Name $ Height Weight @@;
datalines;
Alfred 69.0 112.5 Alice 56.5 84.0 Barbara 65.3 98.0
Carol 62.8 102.5 Henry 63.5 102.5 James 57.3 83.0
Jane 59.8 84.5 Janet 62.5 112.5 Jeffrey 62.5 84.0
John 59.0 99.5 Joyce 51.3 50.5 Judy 64.3 90.0
Louise 56.3 77.0 Mary 66.5 112.0 Philip 72.0 150.0
Robert 64.8 128.0 Ronald 67.0 133.0 Thomas 57.5 85.0
William 66.5 112.0
;
ods graphics on;
proc mcmc data=class outpost=classout nmc=10000 thin=2 seed=246810;
parms beta0 0 beta1 0;
parms sigma2 1;
prior beta0 beta1 ~ normal(mean = 0, var = 1e6);
prior sigma2 ~ igamma(shape = 3/10, scale = 10/3);
mu = beta0 + beta1*height;
model weight ~ n(mu, var = sigma2);
run;
ods graphics off;