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J-GLOBAL ID：201902235218675766   Reference number：19A1528937

An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis

不完全データ解析における補助変数選択のための情報基準【JST・京大機械翻訳】

Author (4)： Imori Shinpei (Graduate School of Science, Hiroshima University, Hiroshima 739-8526, Japan) ,  Imori Shinpei (RIKEN Center for Advanced Intelligence Project, Tokyo 103-0027, Japan) ,  Shimodaira Hidetoshi (Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan) ,  Shimodaira Hidetoshi (RIKEN Center for Advanced Intelligence Project, Tokyo 103-0027, Japan)
Material： Entropy (Web)
Volume： 21  Issue： 3  Page： 281  Publication year： 2019 
JST Material Number： U7179A  ISSN： 1099-4300  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： Statistical inference is consi...

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Thesaurus term： statistical estimation ,  equivalency ,  *formulation ,  simulation ,  model selection ,  estimated accuracy ,  parametric model ,  *variable selection ,  *incomplete data

Author keywords (7)： Akaike information criterion ,  auxiliary variables ,  Fisher information matrix ,  incomplete data ,  Kullback-Leibler divergence ,  misspecification ,  Takeuchi information criterion

JST classification (1)： Quantum optics in general  (BD04010X)

Reference (21)：

• Breiman, L.; Friedman, J.H. Predicting multivariate responses in multiple linear regression. J. R. Stat. Soc. Ser. B Stat. Methodol. 1997, 59, 3-54.
• Tibshirani, R.; Hinton, G. Coaching variables for regression and classification. Stat. Comput. 1998, 8, 25-33.
• Caruana, R. Multitask learning. Mach. Learn. 1997, 28, 41-75.
• Mercatanti, A.; Li, F.; Mealli, F. Improving inference of Gaussian mixtures using auxiliary variables. Stat. Anal. Data Min. 2015, 8, 34-48.
• [Green Version] Kullback, S.; Leibler, R.A. On information and sufficiency. Ann. Math. Stat. 1951, 22, 79-86.

Terms in the title (3)： 不完全データ ,  解析 ,  変数選択