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Model choice in nonnested families
~
Pereira, Carlos Alberto de Braganca.
Model choice in nonnested families
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Model choice in nonnested families/ by Basilio de Braganca Pereira, Carlos Alberto de Braganca Pereira.
Author:
Pereira, Basilio de Braganca.
other author:
Pereira, Carlos Alberto de Braganca.
Published:
Berlin, Heidelberg :Springer Berlin Heidelberg : : 2016.,
Description:
x, 96 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Mathematical statistics. -
Online resource:
http://dx.doi.org/10.1007/978-3-662-53736-7
ISBN:
9783662537367
Model choice in nonnested families
Pereira, Basilio de Braganca.
Model choice in nonnested families
[electronic resource] /by Basilio de Braganca Pereira, Carlos Alberto de Braganca Pereira. - Berlin, Heidelberg :Springer Berlin Heidelberg :2016. - x, 96 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..
Preliminaries -- Frequentist Methods -- Bayesian Methods -- Support and Simulation Methods -- Maximum Likelihood Estimation -- Index.
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.
ISBN: 9783662537367
Standard No.: 10.1007/978-3-662-53736-7doiSubjects--Topical Terms:
527941
Mathematical statistics.
LC Class. No.: QA276
Dewey Class. No.: 519.5
Model choice in nonnested families
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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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Mathematics and Statistics (Springer-11649)
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