Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation (Chapman & Hall/CRC Biostatistics Series)
InBayesian Missing Data Problems, the authors provide a new and appealing approach to handle missing data problems (MDPs), based on noniterative methods. … the examples and real applications following key theorems and concepts are useful for readers to further understand the results and pinpoint major advantages or drawbacks about the proposed methodology. … I recommend this book as a valuable reference for researchers interested in MDPs, and I believe that the methodology described in the book should be included in the up-to-date literature on missing data. … the book stimulated my interest, suggesting an alternative way to think about MDPs. …—Biometrics, June 2011… [this book] sits nicely alongside Tanner’sTools for Statistical Inference. … For those interested in Bayesian computational methods, this book will be of great interest. …—International Statistical Review(2010), 78, 3