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Langue: anglais
Edité par Springer International Publishing AG, CH, 2015
ISBN 10 : 3319189670 ISBN 13 : 9783319189673
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Ajouter au panierTaschenbuch. Etat : Neu. Bayesian Nonparametric Data Analysis | Peter Müller (u. a.) | Taschenbuch | Springer Series in Statistics | xiv | Englisch | 2016 | Springer | EAN 9783319368429 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book's structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.
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Ajouter au panierBuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book's structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.
Langue: anglais
Edité par Springer International Publishing AG, CH, 2015
ISBN 10 : 3319189670 ISBN 13 : 9783319189673
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Ajouter au panierHardcover. Etat : Brand New. 2015 edition. 208 pages. French language. 9.25x6.25x0.50 inches. In Stock.
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Ajouter au panierEtat : new. Questo è un articolo print on demand.
Langue: anglais
Edité par Springer, Springer Jun 2015, 2015
ISBN 10 : 3319189670 ISBN 13 : 9783319189673
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Ajouter au panierBuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book's structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages. 208 pp. Englisch.
Langue: anglais
Edité par Springer, Springer Okt 2016, 2016
ISBN 10 : 3319368427 ISBN 13 : 9783319368429
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book's structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages. 208 pp. Englisch.
Langue: anglais
Edité par Springer International Publishing, 2016
ISBN 10 : 3319368427 ISBN 13 : 9783319368429
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This is the first text to introduce nonparametric Bayesian inference from a data analysis perspectiveIncludes a large number of examples to illustrate the application of nonparametric Bayesian models for important statistical inference Problems.
Langue: anglais
Edité par Springer International Publishing, 2015
ISBN 10 : 3319189670 ISBN 13 : 9783319189673
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This is the first text to introduce nonparametric Bayesian inference from a data analysis perspectiveIncludes a large number of examples to illustrate the application of nonparametric Bayesian models for important statistical inference Problems.
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Ajouter au panierEtat : New. Print on Demand pp. 208.
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. 193.
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. 208.
Langue: anglais
Edité par Springer, Springer Jun 2015, 2015
ISBN 10 : 3319189670 ISBN 13 : 9783319189673
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Ajouter au panierBuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book¿s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 208 pp. Englisch.