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  • 1
    UID:
    almafu_BV014564042
    Umfang: XXVI, 488 S. : , Ill., graph. Darst.
    Ausgabe: 2. ed.
    ISBN: 0-387-95364-7 , 978-0-387-95364-9 , 978-1-4419-2973-0
    Anmerkung: Hier auch später erschienene, unveränderte Nachdrucke
    Weitere Ausg.: Erscheint auch als Online-Ausgabe ISBN 978-0-387-22456-5
    Früher: Früher u.d.T. Burnham, Kenneth P. Model selection and inference
    Sprache: Englisch
    Fachgebiete: Wirtschaftswissenschaften , Biologie , Mathematik
    RVK:
    RVK:
    RVK:
    Schlagwort(e): Modellwahl ; Datenanalyse ; Biologie ; Mathematisches Modell ; Biologie ; Statistik ; Statistik ; Statistik
    URL: Cover
    Mehr zum Autor: Burnham, Kenneth P.
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 2
    UID:
    almahu_9947362741002882
    Umfang: XXVI, 488 p. , online resource.
    Ausgabe: 2.
    ISBN: 9780387224565
    Inhalt: 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.
    Anmerkung: Information and Likelihood Theory: A Basis for Model Selection and Inference -- Basic Use of the Information-Theoretic Approach -- Formal Inference From More Than One Model: Multimodel Inference (MMI) -- Monte Carlo Insights and Extended Examples -- Advanced Issues and Deeper Insights -- Statistical Theory and Numerical Results -- Summary.
    In: Springer eBooks
    Weitere Ausg.: Printed edition: ISBN 9780387953649
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 3
    Online-Ressource
    Online-Ressource
    New York, NY : Springer-Verlag New York, Inc
    UID:
    gbv_1646648625
    Umfang: Online-Ressource , v.: digital
    Ausgabe: 2
    ISBN: 9780387224565
    Serie: Springer eBook Collection
    Inhalt: Information and Likelihood Theory: A Basis for Model Selection and Inference -- Basic Use of the Information-Theoretic Approach -- Formal Inference From More Than One Model: Multimodel Inference (MMI) -- Monte Carlo Insights and Extended Examples -- Advanced Issues and Deeper Insights -- Statistical Theory and Numerical Results -- Summary.
    Inhalt: 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.
    Anmerkung: In: Springer-Online
    Weitere Ausg.: ISBN 9780387953649
    Weitere Ausg.: Buchausg. u.d.T. ISBN 9780387953649
    Sprache: Englisch
    Fachgebiete: Biologie , Mathematik
    RVK:
    RVK:
    Schlagwort(e): Biologie ; Mathematisches Modell ; Biologie ; Statistik
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    Mehr zum Autor: Burnham, Kenneth P.
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 4
    UID:
    b3kat_BV042419028
    Umfang: 1 Online-Ressource (XXVI, 488 S.)
    Ausgabe: 2. ed.
    ISBN: 9780387224565
    Anmerkung: We wrote this book to introduce graduate students and research workers in various scientific 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-defined 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 (multimodel 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 essential expressions and points. Some reorganization has been done to improve the flow 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. Second, concepts related to making formal inferences from more than one model (multimodel inference) have been emphasized throughout the book, but particularly 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 first edition
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-0-387-95364-9
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe ISBN 978-1-4419-2973-0
    Sprache: Englisch
    Fachgebiete: Wirtschaftswissenschaften , Biologie , Mathematik
    RVK:
    RVK:
    RVK:
    RVK:
    Schlagwort(e): Biologie ; Mathematisches Modell ; Modellwahl ; Datenanalyse ; Biologie ; Statistik
    URL: Volltext  (URL des Erstveröffentlichers)
    Mehr zum Autor: Burnham, Kenneth P.
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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