Overview
- Explores the problem of nonnested statistical model choice
- Helps researchers choose between alternative models
- Features various examples and computer simulations
- Presents an account and developments of the methods initially proposed by Sir David Cox
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
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Table of contents (4 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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 Bayes factors and the proposed alternative Bayes factors to overcome these limitations. It also discusses a significance Bayesian procedure. Lastly, Chapter 4 examines the pure likelihood approach. Various real-data examples and computer simulations are provided throughout the text.
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Authors and Affiliations
About the authors
Basilio de Bragança Pereira is a Professor of Biostatistics and of Applied Statistics at the Federal University of Rio de Janeiro in Brazil.
Carlos Alberto de Bragança Pereira is a Professor of Statistics at the University of Sao Paulo in Brazil.
Bibliographic Information
Book Title: Model Choice in Nonnested Families
Authors: Basilio de Bragança Pereira, Carlos Alberto de Bragança Pereira
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-3-662-53736-7
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2016
Softcover ISBN: 978-3-662-53735-0Published: 06 January 2017
eBook ISBN: 978-3-662-53736-7Published: 30 December 2016
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: X, 96
Number of Illustrations: 3 b/w illustrations, 2 illustrations in colour
Topics: Statistical Theory and Methods, Statistics for Business, Management, Economics, Finance, Insurance, Statistics for Life Sciences, Medicine, Health Sciences, Econometrics, Biostatistics, Statistics and Computing/Statistics Programs