Description - Applied Bayesian Hierarchical Methods by Peter D. Congdon
Emphasizing applications and practical computing aspects, this book presents an up-to-date review of Bayesian hierarchical methods. It provides a complete treatment of the main modeling settings, including meta-analysis, time series, nonlinear regression, and multilevel, multivariate, panel, spatial, and survival data. The text includes realistic worked examples from the social and health sciences, mainly employing the WinBUGS package but also incorporating BayesX code. The author also illustrates MCMC sampling from first principles using R. A set of programs linked to the worked examples is available on www.crcpress.com
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Bayesian Hierarchical Models: With Applications Using R, Second Edition
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