FREQUENTIST MODEL AVERAGING ESTIMATION:A REVIEW

查看全文 作　　者：Haiying WANG Xinyu ZHANG Guohua ZOU Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China.

出　　处：《Journal of Systems Science & Complexity》索引2009年第22卷第4期,共17页

基　　金：supported by the National Natural Science Foundation of China under Grant Nos. 70625004, 10721101, and 70221001 摘　　要：In applications, the traditional estimation procedure generally begins with model selection.Once a specific model is selected, subsequent estimation is conducted under the selected model withoutconsideration of the uncertainty from the selection process. This often leads to the underreportingof variability and too optimistic confidence sets. Model averaging estimation is an alternative to thisprocedure, which incorporates model uncertainty into the estimation process. In recent years, therehas been a rising interest in model averaging from the frequentist perspective, and some importantprogresses have been made. In this paper, the theory and methods on frequentist model averagingestimation are surveyed. Some future research topics are also discussed. 关键词：估计模型 T模型平均展望不确定性模型选择 t模型程序

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FREQUENTIST MODEL AVERAGING ESTIMATION:A REVIEW

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