The EM algorithm and extensions
By: Geoffrey J. McLachlan, Thriyambakam Krishnan.
Contributors: Krishnan, T. 1938-
Edition: 2nd ed.
Publisher: John Wiley
Published: 2007
Place of publication: Hoboken, N.J
Language: eng
Number of pages: 359
ISBN-13: 9780471201700
Subjects: Expectation-maximization algorithms; Estimation theory; Missing observations (Statistics)
Description: "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."--Jacket.