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In den WarenkorbEinband - flex.(Paperback). Zustand: New. This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a resource that I am certain will be used by researchers in statistics and related disciplines for quite some ti.
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In den WarenkorbZustand: New. Paul D. McNicholas is the Canada Research Chair in Computational Statistics at McMaster University, where he is a Professor in the Department of Mathematics and Statistics. Peter Tait is a Ph.D. student at the Department of.
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Taschenbuch. Zustand: Neu. Mixture Model-Based Classification | Paul D. McNicholas | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | Taylor & Francis Ltd | EAN 9780367736958 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Sprache: Englisch
Verlag: Taylor & Francis Jan 2019, 2019
ISBN 10: 1138499986 ISBN 13: 9781138499980
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware.
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In den WarenkorbZustand: New. This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a resource that I am certain will be used by researchers in statistics and related disciplines for quite some ti.
Buch. Zustand: Neu. Neuware - 'This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a resource that I am certain will be used by researchers in statistics and related disciplines for quite some time. The discussion of mixtures with heavy tails and asymmetric distributions will place this text as the authoritative, modern reference in the mixture modeling literature.' (Douglas Steinley, University of Missouri)Mixture Model-Based Classification is the first monograph devoted to mixture model-based approaches to clustering and classification. This is both a book for established researchers and newcomers to the field. A history of mixture models as a tool for classification is provided and Gaussian mixtures are considered extensively, including mixtures of factor analyzers and other approaches for high-dimensional data. Non-Gaussian mixtures are considered, from mixtures with components that parameterize skewness and/or concentration, right up to mixtures of multiple scaled distributions. Several other important topics are considered, including mixture approaches for clustering and classification of longitudinal data as well as discussion about how to define a clusterPaul D. McNicholas is the Canada Research Chair in Computational Statistics at McMaster University, where he is a Professor in the Department of Mathematics and Statistics. His research focuses on the use of mixture model-based approaches for classification, with particular attention to clustering applications, and he has published extensively within the field. He is an associate editor for several journals and has served as a guest editor for a number of special issues on mixture models.
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In den WarenkorbZustand: New. Paul D. McNicholas is the Canada Research Chair in Computational Statistics at McMaster University, where he is a Professor in the Department of Mathematics and Statistics. Peter Tait is a Ph.D. student at the Department of.
Sprache: Englisch
Verlag: Taylor & Francis Ltd Dez 2018, 2018
ISBN 10: 1138499994 ISBN 13: 9781138499997
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware.
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2025
ISBN 10: 303203843X ISBN 13: 9783032038432
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In den WarenkorbHardcover. Zustand: Brand New. 350 pages. 9.26x6.11x9.25 inches. In Stock.