Model Selection Averaging by Gerda Claeskens (22 results)

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Hardback. Condition: New. Given a data set, you can fit thousands of models at the push of a button, but how do you choose the best? With so many candidate models, overfitting is a real danger. Is the monkey who typed Hamlet actually a good writer? Choosing a model is central to all statistical work with data. We have seen rapid advances in model fitting and in the theoretical understanding of model selection, yet this book is the first to synthesize research and practice from this active field. Model choice criteria are explained, discussed and compared, including the AIC, BIC, DIC and FIC. The uncertainties involved with model selection are tackled, with discussions of frequentist and Bayesian methods; model averaging schemes are presented. Real-data examples are complemented by derivations providing deeper insight into the methodology, and instructive exercises build familiarity with the methods. The companion website features Data sets and R code.…

Condition: New. pp. 332 Index.

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Condition: New. 2008. 1st Edition. Hardcover. First book to synthesize the research and practice from the active field of model selection. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 332 pages, 46 b/w illus. 35 tables 65 exercises. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 262 x 185 x 27. Weight in Grams: 788. Series: Cambridge Series in Statistical and Probabilistic Mathematics. 320 pages, 46 b/w illus. 35 tables 65 exercises. First book to synthesize the research and practice from the active field of model selection. Cateogry: (P) Professional & Vocational. BIC Classification: PBT. Dimension: 262 x 185 x 27. Weight: 866. . . . . . Books ship from the US and Ireland. …

Hardback. Condition: New. Given a data set, you can fit thousands of models at the push of a button, but how do you choose the best? With so many candidate models, overfitting is a real danger. Is the monkey who typed Hamlet actually a good writer? Choosing a model is central to all statistical work with data. We have seen rapid advances in model fitting and in the theoretical understanding of model selection, yet this book is the first to synthesize research and practice from this active field. Model choice criteria are explained, discussed and compared, including the AIC, BIC, DIC and FIC. The uncertainties involved with model selection are tackled, with discussions of frequentist and Bayesian methods; model averaging schemes are presented. Real-data examples are complemented by derivations providing deeper insight into the methodology, and instructive exercises build familiarity with the methods. The companion website features Data sets and R code.…

Condition: New. 2008. 1st Edition. Hardcover. First book to synthesize the research and practice from the active field of model selection. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 332 pages, 46 b/w illus. 35 tables 65 exercises. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 262 x 185 x 27. Weight in Grams: 788. Series: Cambridge Series in Statistical and Probabilistic Mathematics. 320 pages, 46 b/w illus. 35 tables 65 exercises. First book to synthesize the research and practice from the active field of model selection. Cateogry: (P) Professional & Vocational. BIC Classification: PBT. Dimension: 262 x 185 x 27. Weight: 866. . . . . . …

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Condition: New. Print on Demand pp. 332 Illus.

Hardcover. Condition: new. Hardcover. Given a data set, you can fit thousands of models at the push of a button, but how do you choose the best? With so many candidate models, overfitting is a real danger. Is the monkey who typed Hamlet actually a good writer? Choosing a model is central to all statistical work with data. We have seen rapid advances in model fitting and in the theoretical understanding of model selection, yet this book is the first to synthesize research and practice from this active field. Model choice criteria are explained, discussed and compared, including the AIC, BIC, DIC and FIC. The uncertainties involved with model selection are tackled, with discussions of frequentist and Bayesian methods; model averaging schemes are presented. Real-data examples are complemented by derivations providing deeper insight into the methodology, and instructive exercises build familiarity with the methods. The companion website features Data sets and R code. Choosing a model is central to all statistical work with data; this book is the first to synthesize research and practice from this active field. Model choice criteria are explained, discussed and compared, including the AIC, BIC, DIC and FIC. Real-data examples and exercises build familiarity with the methods. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Choosing a model is central to all statistical work with data this book is the first to synthesize research and practice from this active field. Model choice criteria are explained, discussed and compared, including the AIC, BIC, DIC and FIC. Real-data exa. …

Condition: New. PRINT ON DEMAND pp. 332.

Buch. Condition: Neu. Model Selection and Model Averaging | Gerda Claeskens (u. a.) | Buch | Englisch | 2014 | Cambridge University Press | EAN 9780521852258 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.