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Model choice in nonnested families

Author: Basilio de Bragança Pereira; Carlos Alberto de Bragança Pereira
Publisher: Berlin, Germany : Springer, ©2016.
Series: SpringerBriefs in statistics.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book discusses the problem of model choice when the statistical models are separate, also called nonnested. Chapter 1 provides an introduction, motivating examples and a general overview of the problem. Chapter 2 presents the classical or frequentist approach to the problem as well as several alternative procedures and their properties. Chapter 3 explores the Bayesian approach, the limitations of the classical  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Pereira, Basilio de Bragança.
Model choice in nonnested families.
Berlin, Germany : Springer, 2016
(OCoLC)959596456
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Basilio de Bragança Pereira; Carlos Alberto de Bragança Pereira
ISBN: 9783662537367 3662537362
OCLC Number: 967679600
Description: 1 online resource (x, 96 pages) : illustrations (some color)
Contents: Preface; Contents; 1 Preliminaries; 1.1 Model Choice; 1.2 Types of Problems; 1.3 General Formulation; 1.4 Plan of the Book; 1.5 Bibliographic Notes; References; 2 Frequentist Methods; 2.1 Introduction; 2.2 The Cox Test; 2.2.1 Preliminaries; 2.2.2 Remarks on the Distribution of Tfg; 2.2.3 The Test Procedure; 2.3 A Test Based on a Compound Model; 2.4 Alternative Tests; 2.4.1 Test for Multiple Hypotheses; 2.4.2 Test Based on Nondirectional Divergence; 2.4.3 Test of the Nearest Alternative; 2.4.4 Test Based on the Moment Generating Function; 2.4.5 Two Further Tests. 2.5 Efficiencies of False Separate Models2.5.1 Introduction; 2.5.2 Efficiency of a false regression model; 2.6 Properties and Comparisons; 2.6.1 Asymptotic Power; 2.6.2 Monte Carlo Comparison and Behavior; 2.6.3 Test Consistency and Finite-Sample Results; 2.7 Bibliographic Notes; References; 3 Bayesian Methods; 3.1 Introduction; 3.2 Modified Bayes Factors; 3.2.1 Imaginary Training Sample; 3.2.2 Partial Bayes Factor (PBF); 3.2.3 Fractional Bayes Factor (FBF); 3.2.4 Intrinsic Bayes Factor (IBF); 3.2.5 Posterior Bayes Factor (POBF); 3.2.6 Applications; 3.3 Full Bayesian Significance Test (FBST). 3.4 Bibliographic NotesReferences; 4 Support and Simulation Methods; 4.1 Introduction; 4.2 Likelihood Inference; 4.3 Simulations and Bootstrap; 4.3.1 Simulations; 4.3.2 Bootstrap; 4.3.3 Applications; 4.4 Bibliographic Notes; References; Appendix A Maximum Likelihood Estimation (MLE); Index.
Series Title: SpringerBriefs in statistics.
Responsibility: Basilio de Bragança Pereira, Carlos Alberto de Bragança Pereira.

Abstract:

This book discusses the problem of model choice when the statistical models are separate, also called nonnested. Chapter 3 explores the Bayesian approach, the limitations of the classical Bayes  Read more...

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"The authors are recognized experts teaching statistics in Brazil universities, and in the book ... they present various methods of choosing between competing families of regression models, for Read more...

 
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