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  1. Bog
  2. Matematik
  3. Sandsynlighedsregning og statistik
Bayesian Missing Data Problems
- EM, Data Augmentation and Noniterative Computation
Af: Ming T. Tan, Kai Wang Ng, Guo-Liang Tian
Engelsk
Bogcover for Bayesian Missing Data Problems af Ming T. Tan, Kai Wang Ng, Guo-Liang Tian, 9780367385309
Specifikationer
Sprog:
Engelsk
Sider:
346
ISBN-13:
9780367385309
Indbinding:
Paperback
ISBN-10:
0367385309
Kategori:
Udg. Dato:
4 nov 2019
Størrelse i cm:
23,4 x 15,6
Forlag:
Oplagsdato:
4 nov 2019
Forfatter(e):
Genre:

Bayesian Missing Data Problems

- EM, Data Augmentation and Noniterative Computation
Af: Ming T. Tan, Kai Wang Ng, Guo-Liang Tian
Engelsk
Paperback 2019
Format:
Paperback
Bog beskrivelse

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.

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Specifikationer
Sprog:
Engelsk
Sider:
346
ISBN-13:
9780367385309
Indbinding:
Paperback
ISBN-10:
0367385309
Kategori:
Udg. Dato:
4 nov 2019
Størrelse i cm:
23,4 x 15,6
Forlag:
Oplagsdato:
4 nov 2019
Forfatter(e):
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