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Description
The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book is the first to offer a systematic presentation of the Bayesian perspective of finite mixture modelling. The book is designed to show finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated. Presenting its concepts informally without sacrificing mathematical correctness, it will serve a wide readership including statisticians as well as biologists, economists, engineers, financial and market researchers.
Pages
494 pages
Collection
Springer Series in Statistics
Parution
2006-11-24
Marque
Springer
EAN papier
9780387329093
EAN PDF
9780387357683

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
49
Taille du fichier
5489 Ko
Prix
210,99 €