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FREQUENTIST MODEL AVERAGING ESTIMATION: A REVIEW

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文摘 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 without consideration of the uncertainty from the selection process. This often leads to the underreporting of variability and too optimistic confidence sets. Model averaging estimation is an alternative to this procedure, which incorporates model uncertainty into the estimation process. In recent years, there has been a rising interest in model averaging from the frequentist perspective, and some important progresses have been made. In this paper, the theory and methods on frequentist model averaging estimation are surveyed. Some future research topics are also discussed.
来源 Journal of Systems Science and Complexity ,2009,22(4):732-748 【核心库】
DOI 10.1007/s11424-009-9198-y
关键词 Adaptive regression ; asymptotic theory ; frequentist model averaging ; model selection ; optimality
地址

Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190

语种 英文
文献类型 研究性论文
ISSN 1009-6124
学科 自动化技术、计算机技术
基金 国家自然科学基金
文献收藏号 CSCD:3771287

参考文献 共 49 共3页

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