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Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation by Ming T. Tan, Guo-Liang Tian, Kai Wang Ng (Hardcover, 2009)

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Title: Bayesian Missing Data Problems (Chapman & Hall/CRC Biostatistics Item Condition: New. Author: Ming T. Tan, Guo-Liang Tian, Kai Wang Ng ISBN 10: 142007749X. Publisher: Chapman and Hall/CRC ISBN 13: 9781420077490. ).

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Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors. The methods are based on the inverse Bayes formulae discovered by one of the author in 1995. Applying the Bayesian approach to important real-world problems, the authors focus on exact numerical solutions, a conditional sampling approach via data augmentation, and a noniterative sampling approach via EM-type algorithms. After introducing the missing data problems, Bayesian approach, and posterior computation, the book succinctly describes EM-type algorithms, Monte Carlo simulation, numerical techniques, and optimization methods. It then gives exact posterior solutions for problems, such as nonresponses in surveys and cross-over trials with missing values. It also provides noniterative posterior sampling solutions for problems, such as contingency tables with supplemental margins, aggregated responses in surveys, zero-inflated Poisson, capture-recapture models, mixed effects models, right-censored regression model, and constrained parameter models. The text concludes with a discussion on compatibility, a fundamental issue in Bayesian inference. This book offers a unified treatment of an array of statistical problems that involve missing data and constrained parameters. It shows how Bayesian procedures can be useful in solving these problems.

Product Identifiers

Publisher
Taylor & Francis LTD
ISBN-13
9781420077490
eBay Product ID (ePID)
91476679

Product Key Features

Author
Ming T. Tan, Guo-Liang Tian, Kai Wang Ng
Publication Name
Bayesian Missing Data Problems: Em, Data Augmentation and Noniterative Computation
Format
Hardcover
Language
English
Subject
Biology, Mathematics
Publication Year
2009
Type
Textbook
Number of Pages
346 Pages

Dimensions

Item Height
234mm
Item Width
156mm
Item Weight
635g

Additional Product Features

Title_Author
Kai Wang Ng, Ming T. Tan, Guo-Liang Tian
Country/Region of Manufacture
United States

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Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation by Ming T. Tan, Guo-Liang Tian, Kai Wang Ng (Hardcover, 2009)

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