03140cam a22004214a 45000010005000000030009000050050017000140080041000310100017000720200026000890200023001150350024001380350019001620400059001810410008002400500024002480820026002721000035002982450085003332500012004182600049004303000036004794400047005155000138005625040066007005050283007665201080010495260008021296500041021376500023021786500038022017000041022398560083022808560106023638560091024698560105025608560053026657313BD-DhEWU20180129121018.0131231s2008 njua g b 001 0 eng d a 2007017908 a9780471201700 (cloth) a0471201707 (cloth) a(OCoLC)ocn137325058 a(BD-DhEWU)7313 aDLCcDLCdBTCTAdBAKERdYDXCPdC#PdDLCdBD-DhEWUbeng aeng00aQA276.8b.M394 200804a519.544 MCE222b20081 aMcLachlan, Geoffrey J.,d1946-14aThe EM algorithm and extensions /cGeoffrey J. McLachlan, Thriyambakam Krishnan. a2nd ed. aHoboken, N.J. :bWiley-Interscience,cc2008. axxvii, 359 p. :bill. ;c24 cm. 0aWiley series in probability and statistics aOnline version:
McLachlan, Geoffrey J., 1946-
EM algorithm and extensions.
Hoboken, N.J. : Wiley-Interscience, c2008
(OCoLC)654674444 aIncludes bibliographical references (p. 311-337) and indexes. aExamples 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. a"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. aCSE 0aExpectation-maximization algorithms. 0aEstimation theory. 0aMissing observations (Statistics)1 aKrishnan, T.q(Thriyambakam),d1938-413Table of contents onlyuhttp://www.loc.gov/catdir/toc/ecip0716/2007017908.html423Contributor biographical informationuhttp://www.loc.gov/catdir/enhancements/fy0814/2007017908-b.html423Publisher descriptionuhttp://www.loc.gov/catdir/enhancements/fy0814/2007017908-d.html423OCLCuhttp://www.worldcat.org/title/em-algorithm-and-extensions/oclc/137325058&referer=brief_results423E-book Fulltextuhttp://lib.ewubd.edu/ebook/7313