Model selection and model averaging /:
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 suitable model is central to all statistical work with...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge ; New York :
Cambridge University Press,
2008.
|
| Schriftenreihe: | Cambridge series on statistical and probabilistic mathematics.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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 suitable model is central to all statistical work with data. Selecting the variables for use in a regression model is one important example. The past two decades have seen rapid advances both in our ability to fit models and in the theoretical understanding of model selection needed to harness this ability, yet this book is the first to provide a synthesis of research from this active field, and it contains much material previously difficult or impossible to find. In addition, it gives practical advice to the researcher confronted with conflicting results." "Model choice criteria are explained, discussed and compared, including Akaike's information criterion AIC, the Bayesian information criterion BIC and the focused information criterion FIC. Importantly, the uncertainties involved with model selection are addressed, with discussions of frequentist and Bayesian methods. Finally, model averaging schemes, which combine the strengths of several candidate models, are presented."--Jacket |
| Beschreibung: | 1 online resource (xvii, 312 pages) : illustrations |
| Bibliographie: | Includes bibliographical references (pages 293-305) and indexes. |
| ISBN: | 9780511424106 0511424108 0511423624 9780511423628 9780511422430 0511422431 9780511790485 0511790481 9780511421235 0511421230 0511423098 9780511423093 |
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| 504 | |a Includes bibliographical references (pages 293-305) and indexes. | ||
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| author | Claeskens, Gerda, 1973- Hjort, Nils Lid |
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| contents | Model selection : data examples and introduction -- Akaike's information criterion -- The Bayesian information criterion -- A comparison of some selection methods -- Bigger is not always better -- The focussed information criterion -- Frequentist and Bayesian model averaging -- Lack-of-fit and goodness-of-fit tests -- Model selection and averaging schemes in action -- Further topics. |
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| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
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| discipline | Mathematik Wirtschaftswissenschaften |
| format | Electronic eBook |
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| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-4-EBA-ocn289117359 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:16:36Z |
| institution | BVB |
| isbn | 9780511424106 0511424108 0511423624 9780511423628 9780511422430 0511422431 9780511790485 0511790481 9780511421235 0511421230 0511423098 9780511423093 |
| language | English |
| oclc_num | 289117359 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (xvii, 312 pages) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Cambridge University Press, |
| record_format | marc |
| series | Cambridge series on statistical and probabilistic mathematics. |
| series2 | Cambridge series in statistical and probabilistic mathematics |
| spelling | Claeskens, Gerda, 1973- author. https://id.oclc.org/worldcat/entity/E39PBJfWVPGVGTxyrkwxDqpByd http://id.loc.gov/authorities/names/n2008010287 Model selection and model averaging / Gerda Claeskens, K.U. Leuven, Nils Lid Hjort, University of Oslo. Cambridge ; New York : Cambridge University Press, 2008. ©2008 1 online resource (xvii, 312 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Cambridge series in statistical and probabilistic mathematics 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 suitable model is central to all statistical work with data. Selecting the variables for use in a regression model is one important example. The past two decades have seen rapid advances both in our ability to fit models and in the theoretical understanding of model selection needed to harness this ability, yet this book is the first to provide a synthesis of research from this active field, and it contains much material previously difficult or impossible to find. In addition, it gives practical advice to the researcher confronted with conflicting results." "Model choice criteria are explained, discussed and compared, including Akaike's information criterion AIC, the Bayesian information criterion BIC and the focused information criterion FIC. Importantly, the uncertainties involved with model selection are addressed, with discussions of frequentist and Bayesian methods. Finally, model averaging schemes, which combine the strengths of several candidate models, are presented."--Jacket Includes bibliographical references (pages 293-305) and indexes. Model selection : data examples and introduction -- Akaike's information criterion -- The Bayesian information criterion -- A comparison of some selection methods -- Bigger is not always better -- The focussed information criterion -- Frequentist and Bayesian model averaging -- Lack-of-fit and goodness-of-fit tests -- Model selection and averaging schemes in action -- Further topics. Print version record. Mathematical models Research. Mathematical statistics Research. Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Modèles mathématiques Recherche. Statistique mathématique Recherche. Théorie de la décision bayésienne. MATHEMATICS Probability & Statistics General. bisacsh Bayesian statistical decision theory fast Mathematical models Research fast Mathematical statistics Research fast Statistisches Modell gnd http://d-nb.info/gnd/4121722-6 Electronic books. Hjort, Nils Lid, author. http://id.loc.gov/authorities/names/nb91406389 has work: Model selection and model averaging (Text) https://id.oclc.org/worldcat/entity/E39PCFKCrTQF7RJtPKwmFgdrmb https://id.oclc.org/worldcat/ontology/hasWork Print version: Claeskens, Gerda, 1973- Model selection and model averaging. Cambridge ; New York : Cambridge University Press, 2008 9780521852258 0521852250 (DLC) 2008006507 (OCoLC)199455609 Cambridge series on statistical and probabilistic mathematics. http://id.loc.gov/authorities/names/n96064948 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=244506 Volltext |
| spellingShingle | Claeskens, Gerda, 1973- Hjort, Nils Lid Model selection and model averaging / Cambridge series on statistical and probabilistic mathematics. Model selection : data examples and introduction -- Akaike's information criterion -- The Bayesian information criterion -- A comparison of some selection methods -- Bigger is not always better -- The focussed information criterion -- Frequentist and Bayesian model averaging -- Lack-of-fit and goodness-of-fit tests -- Model selection and averaging schemes in action -- Further topics. Mathematical models Research. Mathematical statistics Research. Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Modèles mathématiques Recherche. Statistique mathématique Recherche. Théorie de la décision bayésienne. MATHEMATICS Probability & Statistics General. bisacsh Bayesian statistical decision theory fast Mathematical models Research fast Mathematical statistics Research fast Statistisches Modell gnd http://d-nb.info/gnd/4121722-6 |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85012506 http://d-nb.info/gnd/4121722-6 |
| title | Model selection and model averaging / |
| title_auth | Model selection and model averaging / |
| title_exact_search | Model selection and model averaging / |
| title_full | Model selection and model averaging / Gerda Claeskens, K.U. Leuven, Nils Lid Hjort, University of Oslo. |
| title_fullStr | Model selection and model averaging / Gerda Claeskens, K.U. Leuven, Nils Lid Hjort, University of Oslo. |
| title_full_unstemmed | Model selection and model averaging / Gerda Claeskens, K.U. Leuven, Nils Lid Hjort, University of Oslo. |
| title_short | Model selection and model averaging / |
| title_sort | model selection and model averaging |
| topic | Mathematical models Research. Mathematical statistics Research. Bayesian statistical decision theory. http://id.loc.gov/authorities/subjects/sh85012506 Modèles mathématiques Recherche. Statistique mathématique Recherche. Théorie de la décision bayésienne. MATHEMATICS Probability & Statistics General. bisacsh Bayesian statistical decision theory fast Mathematical models Research fast Mathematical statistics Research fast Statistisches Modell gnd http://d-nb.info/gnd/4121722-6 |
| topic_facet | Mathematical models Research. Mathematical statistics Research. Bayesian statistical decision theory. Modèles mathématiques Recherche. Statistique mathématique Recherche. Théorie de la décision bayésienne. MATHEMATICS Probability & Statistics General. Bayesian statistical decision theory Mathematical models Research Mathematical statistics Research Statistisches Modell Electronic books. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=244506 |
| work_keys_str_mv | AT claeskensgerda modelselectionandmodelaveraging AT hjortnilslid modelselectionandmodelaveraging |