Handbook of Mixture Analysis (ePub)
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This handbook is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy.
Gilles Celeux is Director of research emeritus with INRIA Saclay-Île-de-France, France. He has conducted research in statistical learning, model-based clustering and model selection for more than 35 years and he leaded to Inria teams. His first paper on mixture modelling was written in 1981 and he is one of the co-organisators of the summer working group on model-based clustering since 1994. He has published more than 40 papers in international Journals of Statistics and wrote two textbooks in French on Classification. He was Editor-in-Chief of Statistics and Computing between 2006 and 2012 and he is the present Editor-in-Chief of the Journal of the French Statistical Society since 2012.
Christian P. Robert is Professor of Mathematics at CEREMADE, Université Paris-Dauphine, PSL Research University, France, and Professor of Statistics at the Department of Statistics, University of Warwick, UK. He has conducted research in Bayesian inference and computational methods covering Monte Carlo, MCMC, and ABC techniques, for more than 30 years, writing The Bayesian Choice (2001) and Monte Carlo
- 2019, 1. Auflage, 522 Seiten, Englisch
- Herausgegeben: Sylvia Fruhwirth-Schnatter, Gilles Celeux, Christian P. Robert
- Verlag: Taylor & Francis
- ISBN-10: 0429508867
- ISBN-13: 9780429508868
- Erscheinungsdatum: 04.01.2019
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- Dateiformat: ePub
- Größe: 20 MB
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