Bayesian statistical modelling (Q2712594)

The book under review aims to contribute to the development of accessible software methods for applying Bayesian methodology. The author discusses several major areas of statistical applications and modeling with the view to implementing components of the Bayesian perspective and to developing source code in the WINBUGS program, which may be extended to similar problems by students and researchers. The book consists of the following ten chapters:NEWLINENEWLINENEWLINEChapter 1. Introduction: The Bayesian method, its benefits and implementation; Chapter 2. Standard distributions: updating, inference and prediction; Chapter 3. Models for association and classification; Chapter 4. Normal linear regression, general linear models and log-linear models; Chapter 5. Ensemble estimates: hierarchical priors for pooling strength; Chapter 6. Latent variables, mixture analysis and models for nonresponse; Chapter 7. Correlated data models; Chapter 8. Multilevel models, multivariate analysis and longitudinal models; Chapter 9. Life tables and survival analysis; Chapter 10. Bayesian estimation and model assessment.