The EM Algorithm and Related Statistical Models (ePub)
(Sprache: Englisch)
Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method for constructing statistical models when only incomplete information is available, and proposes specific estimation...
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Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method for constructing statistical models when only incomplete information is available, and proposes specific estimation algorithms for solutions to incomplete data problems. The text covers current topics including statistical models with latent variables, as well as neural network models, and Markov Chain Monte Carlo methods. It describes software resources valuable for the processing of the EM algorithm with incomplete data and for general analysis of latent structure models of categorical data, and studies accelerated versions of the EM algorithm.
Autoren-Porträt
Michiko Watanabe is Professor, Faculty of Economics, Toyo University, Japan. An elected member of the International International Statistics Institute (1999) and a council member of the Japan Statistical Society (2000), she received the Ph.D. degree (1988) from Kyushu University, Japan. Kazunori Yamaguchi is Professor, College of Social Relations, Rikkyo University, Japan. An elected member of the International Statistics Institute (1999) and a council member of the Japan Statistical Society (2000-2001), he received the Ph.D. degree (1991) from Kyushu University, Japan.
Bibliographische Angaben
- 2003, 250 Seiten, Englisch
- Herausgegeben: Michiko Watanabe, Kazunori Yamaguchi
- Verlag: Taylor & Francis
- ISBN-10: 1135524661
- ISBN-13: 9781135524661
- Erscheinungsdatum: 15.10.2003
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eBook Informationen
- Dateiformat: ePub
- Grösse: 11 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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