Model choice in nonnested families
Language: English Series: Springer briefs in statisticsPublication details: Springer 2016 BerlinDescription: x,96pISBN:- 9783662537350
- 519.5 P414m
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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PK Kelkar Library, IIT Kanpur | General Stacks | 519.5 P414m (Browse shelf(Opens below)) | Available | A183390 |
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519.5 Og9r Random phenomena | 519.5 Op7 Optimal design and analysis of experiments | 519.5 P193s Statistical inference | 519.5 P414m Model choice in nonnested families | 519.5 P448d Dynamic linear models with R | 519.5 P544s Statistical thinking | 519.5 P683s Some basic theory for statistical inference |
Includes bibliographical references and index
his 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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