ISBN: 9781441929730 - model selection and multimodel inference: a practical information-theoretic approach (16 risultati)

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  • Lingua: Inglese

    Editore: Springer (edition ), 2010

    1441929738 / 9781441929730

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    Paperback. Condizione: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

  • Lingua: Inglese

    Editore: Springer, 2010

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  • Lingua: Inglese

    Editore: Springer, 2010

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  • Lingua: Inglese

    Editore: Springer, 2010

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  • Lingua: Inglese

    Editore: Springer, 2010

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer-Verlag New York Inc., US, 2010

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    Paperback. Condizione: New. Statisticians and applied scientists often must select a model to fit empirical data. This book introduces researchers and graduate students in many areas to an information criterion approach, first introduced by Hirotugu Akaike in 1973. The book will be of general interest, but the emphasis is on applications to the biological sciences. Softcover reprint of the original 2nd ed. 2002.…

  • Lingua: Inglese

    Editore: Springer, 2010

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - We wrote this book to introduce graduate students and research workers in various scienti c disciplines to the use of information-theoretic approaches in the analysis of empirical data. These methods allow the data-based selection of a 'best' model and a ranking and weighting of the remaining models in a pre-de ned set. Traditional statistical inference can then be based on this selected best model. However, we now emphasize that information-theoretic approaches allow formal inference to be based on more than one model (m- timodel inference). Such procedures lead to more robust inferences in many cases, and we advocate these approaches throughout the book. The second edition was prepared with three goals in mind. First, we have tried to improve the presentation of the material. Boxes now highlight ess- tial expressions and points. Some reorganization has been done to improve the ow of concepts, and a new chapter has been added. Chapters 2 and 4 have been streamlined in view of the detailed theory provided in Chapter 7. S- ond, concepts related to making formal inferences from more than one model (multimodel inference) have been emphasized throughout the book, but p- ticularly in Chapters 4, 5, and 6. Third, new technical material has been added to Chapters 5 and 6. Well over 100 new references to the technical literature are given. These changes result primarily from our experiences while giving several seminars, workshops, and graduate courses on material in the rst e- tion.…

  • Lingua: Inglese

    Editore: Springer-Verlag New York Inc., US, 2010

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    Paperback. Condizione: New. Statisticians and applied scientists often must select a model to fit empirical data. This book introduces researchers and graduate students in many areas to an information criterion approach, first introduced by Hirotugu Akaike in 1973. The book will be of general interest, but the emphasis is on applications to the biological sciences. Softcover reprint of the original 2nd ed. 2002.…

  • Lingua: Inglese

    Editore: Springer, 2010

    1441929738 / 9781441929730

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    Paperback. Condizione: new. New Copy. Customer Service Guaranteed.

  • Lingua: Inglese

    Editore: Springer, 2010

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  • Lingua: Inglese

    Editore: Springer, 2010

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  • Lingua: Inglese

    Editore: Springer, 2010

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  • Lingua: Inglese

    Editore: Springer, 2010

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  • Lingua: Inglese

    Editore: Springer New York, 2010

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes supplementary material: sn.pub/extrasA unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critica.…

  • Lingua: Inglese

    Editore: Springer, Springer Dez 2010, 2010

    1441929738 / 9781441929730

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We wrote this book to introduce graduate students and research workers in various scienti c disciplines to the use of information-theoretic approaches in the analysis of empirical data. These methods allow the data-based selection of a 'best' model and a ranking and weighting of the remaining models in a pre-de ned set. Traditional statistical inference can then be based on this selected best model. However, we now emphasize that information-theoretic approaches allow formal inference to be based on more than one model (m- timodel inference). Such procedures lead to more robust inferences in many cases, and we advocate these approaches throughout the book. The second edition was prepared with three goals in mind. First, we have tried to improve the presentation of the material. Boxes now highlight ess- tial expressions and points. Some reorganization has been done to improve the ow of concepts, and a new chapter has been added. Chapters 2 and 4 have been streamlined in view of the detailed theory provided in Chapter 7. S- ond, concepts related to making formal inferences from more than one model (multimodel inference) have been emphasized throughout the book, but p- ticularly in Chapters 4, 5, and 6. Third, new technical material has been added to Chapters 5 and 6. Well over 100 new references to the technical literature are given. These changes result primarily from our experiences while giving several seminars, workshops, and graduate courses on material in the rst e- tion. 520 pp. Englisch.…

  • Lingua: Inglese

    Editore: Springer, Humana Dez 2010, 2010

    1441929738 / 9781441929730

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -We wrote this book to introduce graduate students and research workers in various scienti c disciplines to the use of information-theoretic approaches in the analysis of empirical data. These methods allow the data-based selection of a ¿best¿ model and a ranking and weighting of the remaining models in a pre-de ned set. Traditional statistical inference can then be based on this selected best model. However, we now emphasize that information-theoretic approaches allow formal inference to be based on more than one model (m- timodel inference). Such procedures lead to more robust inferences in many cases, and we advocate these approaches throughout the book. The second edition was prepared with three goals in mind. First, we have tried to improve the presentation of the material. Boxes now highlight ess- tial expressions and points. Some reorganization has been done to improve the ow of concepts, and a new chapter has been added. Chapters 2 and 4 have been streamlined in view of the detailed theory provided in Chapter 7. S- ond, concepts related to making formal inferences from more than one model (multimodel inference) have been emphasized throughout the book, but p- ticularly in Chapters 4, 5, and 6. Third, new technical material has been added to Chapters 5 and 6. Well over 100 new references to the technical literature are given. These changes result primarily from our experiences while giving several seminars, workshops, and graduate courses on material in the rst e- tion.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 520 pp. Englisch.…