Stable feature screening for ultrahigh dimensional data |
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Authors: | Peng Lai Fengli Song Yufei Gao |
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Institution: | School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China |
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Abstract: | This paper is concerned with the stable feature screening for the ultrahigh dimensional data. To deal with the ultrahigh dimensional data problem and screen the important features, a set-averaging measurement is proposed. The model averaging technique and the conditional quantile method are used to construct the weighted set-averaging feature screening procedure to identify the relationships between the possible predictors and the response variable. The proposed screening method is model free, stable and possesses the sure screening property under some regular conditions. Some Monte Carlo simulations and a real data application are conducted to evaluate the performance of the proposed procedure. |
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Keywords: | Corresponding author primary 62F07 secondary 62H20 Ultrahigh dimension Set-averaging Feature screening Sure screening property Conditional quantile |
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