 
Summary: MATLAB as an Environment for Bayesian
Computation
Jim Albert 1
Bowling Green State University
July 1997
1 Address for correspondence: Department of Mathematics and Statistics, Bowling Green State
University, Bowling Green, OH 43403, USA.
Abstract
The current status of Bayesian software is reviewed. The motivation for the development of
Bayesian software is described and the software is categorized by the type of user (student,
practitioner, and researcher). The use of the software package MATLAB is illustrated for
the different types of Bayesian software. The use of a MATLAB graphical user interface
(gui) is demonstrated for the introduction of proportion inference using a discrete prior.
A second gui is used to illustrate the use of a MCMC algorithm in logistic modeling with
a data augmented prior. The use of MATLAB as a programming environment for the
development of MCMC algorithms is discussed, and a MCMC program for fitting a random
effects model is outlined.
1 An overview of Bayesian software
