Conditional Akaike information under covariate shift with application to small area estimation |
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| Authors: | Yuki Kawakubo Shonosuke Sugasawa Tatsuya Kubokawa |
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| Affiliation: | 1. Graduate School of Social Sciences, Chiba University, Chiba, Japan;2. Risk Analysis Research Center, The Institute of Statistical Mathematics, Tokyo, Japan;3. Faculty of Economics, The University of Tokyo, Tokyo, Japan |
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| Abstract: | In this study, we consider the problem of selecting explanatory variables of fixed effects in linear mixed models under covariate shift, which is when the values of covariates in the model for prediction differ from those in the model for observed data. We construct a variable selection criterion based on the conditional Akaike information introduced by Vaida & Blanchard (2005). We focus especially on covariate shift in small area estimation and demonstrate the usefulness of the proposed criterion. In addition, numerical performance is investigated through simulations, one of which is a design‐based simulation using a real dataset of land prices. The Canadian Journal of Statistics 46: 316–335; 2018 © 2018 Statistical Society of Canada |
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| Keywords: | Akaike information criterion conditional AIC covariate shift linear mixed model small area estimation MSC 2010: Primary 62J05 secondary 62P25 |
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