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Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation

Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation

Paperback

Series: Chapman & Hall/CRC Biostatistics, Book 32

Medical ReferenceProbability & Statistics

ISBN10: 0367385309
ISBN13: 9780367385309
Publisher: Crc Pr Inc
Published: Nov 4 2019
Pages: 346
Weight: 1.55
Height: 0.80 Width: 6.10 Depth: 9.20
Language: English

This book presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors, based on the inverse Bayes formulae. The authors focus on exact numerical solutions, a conditional sampling approach via data augmentation, and a noniterative sampling approach via EM-type algorithms. They describe Monte Carlo simulation, numerical techniques, and optimization methods. The book illustrates the methods with biostatistical models and real-world applications, including mixed effects and hierarchical models, nonresponse and contingency tables, and the constrained parameter problem reformulated as a missing data problem.

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