Bayesian Modeling Using WinBUGS / Wiley Series in Computational Statistics (ePub)

A hands-on introduction to the principles of Bayesian modeling
using WinBUGS

Bayesian Modeling Using WinBUGS provides an easily
accessible introduction to the use of WinBUGS programming
techniques in a variety of Bayesian modeling settings. The author
provides an accessible treatment of the topic, offering readers a
smooth introduction to the principles of Bayesian modeling with
detailed guidance on the practical implementation of key
principles.

The book begins with a basic introduction to Bayesian inference
and the WinBUGS software and goes on to cover key topics,
including:

* Markov Chain Monte Carlo algorithms in Bayesian inference

* Generalized linear models

* Bayesian hierarchical models

* Predictive distribution and model checking

* Bayesian model and variable evaluation

Computational notes and screen captures illustrate the use of
both WinBUGS as well as R software to apply the discussed
techniques. Exercises at the end of each chapter allow readers to
test their understanding of the presented concepts and all data
sets and code are available on the book's related Web site.

Requiring only a working knowledge of probability theory and
statistics, Bayesian Modeling Using WinBUGS serves as an
excellent book for courses on Bayesian statistics at the
upper-undergraduate and graduate levels. It is also a valuable
reference for researchers and practitioners in the fields of
statistics, actuarial science, medicine, and the social sciences
who use WinBUGS in their everyday work.