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Consistency of the Empirical Bayes Information Criterion for Selecting Variables in Linear Mixed Models

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Author Info
Tatsuya Kubokawa (Faculty of Economics, University of Tokyo)
Muni S. Srivastava (Department of Statistics, University of Toronto)
Abstract

The paper addresses the problem of selecting variables in the two-stage sampling models characterized as a linear mixed model. We obtain the Empirical Bayes Information Criterion (EBIC) using a prior distribution on regression coefficients with an unknown hyper-parameter. It is shown that EBIC not only has the nice asymptotic property of the consistency as a variable selection, but also performs better in small sample sizes than the conventional methods like BIC and AIC in light of selecting the true variables.

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Publisher Info
Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-614.

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Length: 20pages
Date of creation: Feb 2009
Date of revision:
Handle: RePEc:tky:fseres:2009cf614

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This page was last updated on 2009-12-18.


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