Art

J-GLOBAL ID：201202234728465229   Reference number：12A0527015

BAYESIAN VARIABLE SELECTION FOR THE SEEMINGLY UNRELATED REGRESSION MODELS WITH A LARGE NUMBER OF PREDICTORS

多数の予測変数を持つ「見かけ上無関係な回帰」(SUR)モデルに対するBayes型変数選択

Author (1)： ANDO Tomohiro (Keio Univ., Kanagawa, JPN)
Material： Journal of the Japan Statistical Society  (J Jpn Stat Soc)
Volume： 41  Issue： 2  Page： 187-203  Publication year： Dec. 2011 
JST Material Number： L7007A  ISSN： 1882-2754  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： *variable ,  *regression model ,  *Bayes estimation ,  Monte Carlo method ,  *multiple regression analysis ,  parameter estimation
Semi thesaurus term： variable selection ,  *predictor variable

JST classification (1)： Statistics  (AB08000H)

Reference (32)：

• ANDO, T. Hierarchical Bayesian analysis of the seemingly unrelated regression and simultaneous equation models using a combination of a direct Monte Carlo and an importance sampling techniques. Bayesian Analysis. 2010, 5, 65-96
• CARROLL, R. J. Seemingly unrelated measurement error models, with application to nutritional epidemiology. Biometrics. 2006, 62, 75-84
• FRASER, D. A. S. Highly accurate likelihood analysis for the seemingly unrelated regression problem. J. Econom. 2005, 127, 17-33
• GALLANT, R. Seemingly unrelated nonlinear regressions. J. Econom. 1975, 3, 35-50
• GEWEKE, J. Contemporary Bayesian Econometrics and Statistics. 2005

Terms in the title (3)： 予測変数 ,  モデル ,  変数選択