EM ALGORITHMS AND EXTENSIONS

Le Monde En Tique

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Ouvrage 9780471123583 : EM ALGORITHMS AND EXTENSIONS
A unified and complete treatment of the theory and
methodology of the Expectation-Maximization
(EM) algorithm, its extensions and their
applications. Applications in standard statistical contexts
such as regression, factor analysis,
variance-components estimation, repeated-measures designs,
categorical data analysis, survival evaluatio, and
survey sampling are covered, as well as applications
in other areas like genetics and psychometry.
Approximately 30 examples illustrate the theory and
methodology.
Reviews and Commentary
From The Publisher:
A unified and complete treatment of the theory and
methodology of the Expectation-Maximization
(EM) algorithm, its extensions and their
applications. Applications in standard statistical contexts
such as regression, factor analysis,
variance-components estimation, repeated-measures designs,
categorical data analysis, survival evaluatio, and
survey sampling are covered, as well as applications
in other areas like genetics and psychometry.
Approximately 30 examples illustrate the theory and
methodology.
From Booknews:
This volume deals with the Expectation-Maximization
algorithm, now a standard tool applied to
incomplete data problems in virtually every field
in which statistical methods are used. Discussion
covers such topics as regression, categorical data
analysis, factor analysis, variance-components
estimation, repeated-measures designs, medical
imaging, finite mixture analysis, robust statistical
modeling, and survival analysis. Annotation c. by
Book News, Inc., Portland, Or.
Table of Contents
Examples of the EM Algorithm
Basic Theory of the EM Algorithm
Standard Errors and Speeding Up Convergence
Extensions of the EM Algorithm
Miscellaneous Topics
References
Indexes

Auteur : MCLACHLAN
Editeur : JOHN WILEY
Nombre de pages : 380
Date de publication : 10 1996

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