Handbook of mixture analysis. (English) Zbl 1419.62001

Chapman & Hall/CRC Handbooks of Modern Statistical Methods. Boca Raton, FL: CRC Press (ISBN 978-1-4987-6381-3/hbk; 978-0-429-05591-1/ebook). xxiii, 497 p. (2019).

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Publisher’s description: Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time.
The Handbook of Mixture Analysis 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.
The articles of this volume will be reviewed individually.
Indexed articles:
Green, Peter J., Introduction to finite mixtures, 3-20 [Zbl 1428.62274]
Celeux, Gilles, EM methods for finite mixtures, 21-39 [Zbl 1428.62268]
Hunter, David R.; Don, Prabhani Kuruppumullage; Lindsay, Bruce G., An expansive view of EM algorithms, 41-52 [Zbl 1428.62278]
Rousseau, Judith; Grazian, Clara; Lee, Jeong Eun, Bayesian mixture models: theory and methods, 53-72 [Zbl 1428.62295]
Müller, Peter, Bayesian nonparametric mixture models, 97-116 [Zbl 1428.62288]
Celeux, Gilles; Frühwirth-Schnatter, Sylvia; Robert, Christian P., Model selection for mixture models – perspectives and strategies, 117-154 [Zbl 1428.62269]
Grün, Bettina, Model-based clustering, 157-192 [Zbl 1428.62275]
Karlis, Dimitris, Mixture modelling of discrete data, 193-218 [Zbl 1428.62279]
Rossell, David; Steel, Mark F. J., Continuous mixtures with skewness and heavy tails, 219-237 [Zbl 1428.62294]
McParland, Damien; Murphy, Thomas Brendan, Mixture modelling of high-dimensional data, 239-270 [Zbl 1428.62286]
Gormley, Isobel Claire; Frühwirth-Schnatter, Sylvia, Mixture of experts models, 271-307 [Zbl 1428.62273]
Kaufmann, Sylvia, Hidden Markov models in time series, with applications in economics, 309-341 [Zbl 1428.62374]
Gassiat, Elisabeth, Mixtures of nonparametric components and hidden Markov models, 343-360 [Zbl 1428.62272]
Mengersen, Kerrie; Duncan, Earl; Arbel, Julyan; Alston-Knox, Clair; White, Nicole, Applications in industry, 363-383 [Zbl 1428.62513]
Forbes, Florence, Mixture models for image analysis, 385-405 [Zbl 1428.62271]
Maheu, John M.; Zamenjani, Azam Shamsi, Applications in finance, 407-437 [Zbl 1428.62285]
Robin, Stéphane; Ambroise, Christophe, Applications in genomics, 439-461 [Zbl 1428.62479]
Kuhn, Michael A.; Feigelson, Eric D., Applications in astronomy, 463-489 [Zbl 1428.62527]


62-00 General reference works (handbooks, dictionaries, bibliographies, etc.) pertaining to statistics
62-06 Proceedings, conferences, collections, etc. pertaining to statistics
62H30 Classification and discrimination; cluster analysis (statistical aspects)
62P05 Applications of statistics to actuarial sciences and financial mathematics
62M05 Markov processes: estimation; hidden Markov models
00B15 Collections of articles of miscellaneous specific interest


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