Frequentist model averaging estimation: a review |
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Authors: | Haiying Wang Xinyu Zhang Guohua Zou |
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Institution: | (1) Department of Statistics, University of Idaho, Moscow, ID 83844-1104, USA;(2) Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA;(3) Department of Statistics, University of Idaho, Moscow, ID 83844-1104, USA |
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Abstract: | 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. |
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Keywords: | |
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