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The EM algorithm and extensions / Geoffrey J. McLachlan, Thriyambakam Krishnan.

By: McLachlan, Geoffrey J, 1946-Contributor(s): Krishnan, T. (Thriyambakam), 1938-Material type: TextTextLanguage: English Series: Wiley series in probability and statisticsPublication details: Hoboken, N.J. : Wiley-Interscience, c2008. Edition: 2nd edDescription: xxvii, 359 p. : ill. ; 24 cmISBN: 9780471201700 (cloth); 0471201707 (cloth)Subject(s): Expectation-maximization algorithms | Estimation theory | Missing observations (Statistics)DDC classification: 519.544 MCE LOC classification: QA276.8 | .M394 2008Online resources: Table of contents only | Contributor biographical information | Publisher description | OCLC | E-book Fulltext
Contents:
Examples of the EM algorithm -- Basic theory of the EM algorithm -- Standard errors and speeding up convergence -- Extensions of the EM algorithm -- Monte Carlo versions of the EM algorithm -- Some generalizations of the EM algorithm -- Further applications of the EM algorithm.
Summary: "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." "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."--BOOK JACKET.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
E-Book E-Book Dr. S. R. Lasker Library, EWU
E-book
Non-fiction 519.544 MCE 2008 (Browse shelf(Opens below)) Not For Loan
Text Text Dr. S. R. Lasker Library, EWU
Reserve Section
Non-fiction 519.544 MCE 2008 (Browse shelf(Opens below)) C-1 Not For Loan 25610
Text Text Dr. S. R. Lasker Library, EWU
Reserve Section
Non-fiction 519.544 MCE 2008 (Browse shelf(Opens below)) C-2 Not For Loan 26052
Total holds: 0

Online version:
McLachlan, Geoffrey J., 1946-
EM algorithm and extensions.
Hoboken, N.J. : Wiley-Interscience, c2008
(OCoLC)654674444

Includes bibliographical references (p. 311-337) and indexes.

Examples of the EM algorithm --
Basic theory of the EM algorithm --
Standard errors and speeding up convergence --
Extensions of the EM algorithm --
Monte Carlo versions of the EM algorithm --
Some generalizations of the EM algorithm --
Further applications of the EM algorithm.

"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." "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."--BOOK JACKET.

CSE

Tahur Ahmed

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