Model Choice in Nonnested Families

Häftad, Engelska, 2017

Av Basilio de Bragança Pereira, Carlos Alberto de Bragança Pereira, Ca Pereira, Basilio de Bragança

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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.

Produktinformation

Utgivningsdatum2017-01-06
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieSpringerBriefs in Statistics
Antal sidor96
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783662537350

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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 instance, exponential versus lognormal models. … The monograph is interesting, innovative, and can serve in search for adequate models in applied statistical analysis.” (Stan Lipovetsky, Technometrics, Vol. 59 (4), November, 2017)