The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with free, flexible software for the Bayesian analysis of complex statistical models using Markov Chain Monte Carlo (MCMC) methods. It details the various and commonly-used modeling techniques that are employed by statisticians in a multitude of sciences such as; biostatistics and social science; actuarial science environments. This book presents the reader with a clear and easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. Emphasis is given to Generalized Linear Models (GLMs) familiar to most readers and researchers. Detailed explanations cover model building, prior specification, writing WinBUGS code, and analyzing and interpreting WinBUGS output. Also features comprehensive problems and examples.
Keywords: BUGS, Bayesian inference Using Gibbs Sampling, complex statistical models, Markov Chain Monte Carlo, MCMC, WinBUGS programming language, normal regression, generalizedlinear, hierarchal models