Model Selection

Leonhard Held and Daniel Sabanés Bové
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Leonhard Held: University of Zurich, Institute of Social and Preventive Medicine
Daniel Sabanés Bové: University of Zurich, Institute of Social and Preventive Medicine

Chapter 7 in Applied Statistical Inference, 2014, pp 221-245 from Springer

Abstract: Abstract This chapter describes methodology for Model selection both from a likelihood and a Bayesian perspective. In particular, AIC and BIC is discussed and its connection to cross-validation. Bayesian model selection based on the marginal likelihood is described, including Bayesian model averaging. Finally, DIC is introduced, completed by a number of exercises at the end.

Keywords: Prior Distribution; Marginal Likelihood; Deviance Information Criterion; Likelihood Ratio Statistic; Model Selection Criterion (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-37887-4_7

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DOI: 10.1007/978-3-642-37887-4_7

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