## Bayesian Modeling Using WinBUGSA hands-on introduction to the principles of Bayesian modeling using WinBUGS
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, |

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#### Bayesian modeling using WinBUGS

User Review - patrickaz - Overstock.comGreat book for anyone looking to implement Bayesian modeling using the WinBUGS tool. Lots of examples for the specific tool being used are always very helpful. Read full review

### Contents

MARKOV CHAINMONTE CARLO ALGORITHMS | 2-2 |

MISSING OBSERVATIONS USING MCMC | 2-10 |

WinBUGS SOFTWARE INTRODUCTION SETUP | 2-23 |

WinBUGSSOFTWARE ILLUSTRATION RESULTSAND | 15 |

INTRODUCTION TO BAYESIAN MODELS NORMAL | 42 |

SIMPLE MODEL 4 2 FURTHER OUTPUT ANALYSIS USING THE INFERENCE MENU 4 3 MULTIPLE CHAINS | 6-4 |

INCORPORATING CATEGORICAL VARIABLES IN NORMAL MODELSAND FURTHER MODELING ISSUES | 6-6 |

BAYESIAN MODELAND VARIABLE EVALUATION | 6-11 |

INTRODUCTION TOGENERALIZED LINEAR MODELS | 6-32 |