The Em Algorithm and Extensions
Language: English
Published by Wiley Mär 2008, 2008
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
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Add to basketItem description from seller
Neuware - The only single-source--now completely updated and revised--to offer a unified treatment of the theory, methodology, and applications of the EM algorithmComplete with updates that capture developments from the past decade, The EM Algorithm and Extensions, Second Edition successfully provides a basic understanding of the EM algorithm by describing its inception, implementation, and applicability in numerous statistical contexts. In conjunction with the fundamentals of the topic, the authors discuss convergence issues and computation of standard errors, and, in addition, unveil many parallels and connections between the EM algorithm and Markov chain Monte Carlo algorithms. Thorough discussions on the complexities and drawbacks that arise from the basic EM algorithm, such as slow convergence and lack of an in-built procedure to compute the covariance matrix of parameter estimates, are also presented.While the general philosophy of the First Edition has been maintained, this timely new edition has been updated, revised, and expanded to include:\*New chapters on Monte Carlo versions of the EM algorithm and generalizations of the EM algorithm\*New results on convergence, including convergence of the EM algorithm in constrained parameter spaces\*Expanded discussion of standard error computation methods, such as methods for categorical data and methods based on numerical differentiation\*Coverage of the interval EM, which locates all stationary points in a designated region of the parameter space\*Exploration of the EM algorithm's relationship with the Gibbs sampler and other Markov chain Monte Carlo methods\*Plentiful pedagogical elements-chapter introductions, lists of examples, author and subject indices, computer-drawn graphics, and a related Web siteThe EM Algorithm and Extensions, Second Edition serves as an excellent text for graduate-level statistics students and is also a comprehensive resource for theoreticians, practitioners, and researchers in the social and physical sciences who would like to extend their knowledge of the EM algorithm.…
Seller Inventory # 9780471201700
- Title
- The Em Algorithm and Extensions
- Author
- Geoffrey J McLachlan
- Publisher
- Wiley Mär 2008
- Publication year
- 2008
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0471201707
- ISBN 13
- 9780471201700
- Edition
- 2nd Edition
- Item weight
- 765 grams
- Dimensions
- 240x161x26 mm
Complete with updates that capture developments from the past decade, The EM Algorithm and Extensions, Second Edition successfully provides a basic understanding of the EM algorithm by describing its inception, implementation, and applicability in numerous statistical contexts. In conjunction with the fundamentals of the topic, the authors discuss convergence issues and computation of standard errors, and, in addition, unveil many parallels and connections between the EM algorithm and Markov chain Monte Carlo algorithms. Thorough discussions on the complexities and drawbacks that arise from the basic EM algorithm, such as slow convergence and lack of an in-built procedure to compute the covariance matrix of parameter estimates, are also presented.
While the general philosophy of the First Edition has been maintained, this timely new edition has been updated, revised, and expanded to include:
-
New chapters on Monte Carlo versions of the EM algorithm and generalizations of the EM algorithm
-
New results on convergence, including convergence of the EM algorithm in constrained parameter spaces
-
Expanded discussion of standard error computation methods, such as methods for categorical data and methods based on numerical differentiation
-
Coverage of the interval EM, which locates all stationary points in a designated region of the parameter space
-
Exploration of the EM algorithm's relationship with the Gibbs sampler and other Markov chain Monte Carlo methods
-
Plentiful pedagogical elements―chapter introductions, lists of examples, author and subject indices, computer-drawn graphics, and a related Web site
The EM Algorithm and Extensions, Second Edition serves as an excellent text for graduate-level statistics students and is also a comprehensive resource for theoreticians, practitioners, and researchers in the social and physical sciences who would like to extend their knowledge of the EM algorithm.
"Synopsis" may belong to another edition of this title.
About the Author
Thriyambakam Krishnan, PhD, is Chief Statistical Architect, SYSTAT Software at Cranes Software International Limited in Bangalore, India. Dr. Krishnan has over forty-five years of research, teaching, consulting, and software development experience at the Indian Statistical Institute (ISI). His research interests include biostatistics, image analysis, pattern recognition, psychometry, and the EM algorithm.
"About the title" may belong to another edition of this title.
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