Finite Mixture Models
març del 2004 · John Wiley & Sons
Llibre electrònic
464
Pàgines
reportNo es verifiquen les puntuacions ni les ressenyes Més informació
Sobre aquest llibre
An up-to-date, comprehensive account of major issues in finite mixture modeling
This volume provides an up-to-date account of the theory and applications of modeling via finite mixture distributions. With an emphasis on the applications of mixture models in both mainstream analysis and other areas such as unsupervised pattern recognition, speech recognition, and medical imaging, the book describes the formulations of the finite mixture approach, details its methodology, discusses aspects of its implementation, and illustrates its application in many common statistical contexts.
Major issues discussed in this book include identifiability problems, actual fitting of finite mixtures through use of the EM algorithm, properties of the maximum likelihood estimators so obtained, assessment of the number of components to be used in the mixture, and the applicability of asymptotic theory in providing a basis for the solutions to some of these problems. The author also considers how the EM algorithm can be scaled to handle the fitting of mixture models to very large databases, as in data mining applications. This comprehensive, practical guide:
* Provides more than 800 references-40% published since 1995
* Includes an appendix listing available mixture software
* Links statistical literature with machine learning and pattern recognition literature
* Contains more than 100 helpful graphs, charts, and tables
Finite Mixture Models is an important resource for both applied and theoretical statisticians as well as for researchers in the many areas in which finite mixture models can be used to analyze data.
This volume provides an up-to-date account of the theory and applications of modeling via finite mixture distributions. With an emphasis on the applications of mixture models in both mainstream analysis and other areas such as unsupervised pattern recognition, speech recognition, and medical imaging, the book describes the formulations of the finite mixture approach, details its methodology, discusses aspects of its implementation, and illustrates its application in many common statistical contexts.
Major issues discussed in this book include identifiability problems, actual fitting of finite mixtures through use of the EM algorithm, properties of the maximum likelihood estimators so obtained, assessment of the number of components to be used in the mixture, and the applicability of asymptotic theory in providing a basis for the solutions to some of these problems. The author also considers how the EM algorithm can be scaled to handle the fitting of mixture models to very large databases, as in data mining applications. This comprehensive, practical guide:
* Provides more than 800 references-40% published since 1995
* Includes an appendix listing available mixture software
* Links statistical literature with machine learning and pattern recognition literature
* Contains more than 100 helpful graphs, charts, and tables
Finite Mixture Models is an important resource for both applied and theoretical statisticians as well as for researchers in the many areas in which finite mixture models can be used to analyze data.
Sobre l'autor
GEOFFREY McLACHLAN, PhD, DSc, is Professor in the Department of Mathematics at the University of Queensland, Australia.
DAVID PEEL, PhD, is a research fellow in the Department of Mathematics at the University of Queensland, Australia.
DAVID PEEL, PhD, is a research fellow in the Department of Mathematics at the University of Queensland, Australia.
Puntua aquest llibre electrònic
Dona'ns la teva opinió.
Informació de lectura
Telèfons intel·ligents i tauletes
Instal·la l'aplicació Google Play Llibres per a Android i per a iPad i iPhone. Aquesta aplicació se sincronitza automàticament amb el compte i et permet llegir llibres en línia o sense connexió a qualsevol lloc.
Ordinadors portàtils i ordinadors de taula
Pots escoltar els audiollibres que has comprat a Google Play amb el navegador web de l'ordinador.
Lectors de llibres electrònics i altres dispositius
Per llegir en dispositius de tinta electrònica, com ara lectors de llibres electrònics Kobo, hauràs de baixar un fitxer i transferir-lo al dispositiu. Segueix les instruccions detallades del Centre d'ajuda per transferir els fitxers a lectors de llibres electrònics compatibles.
