Variable Selection for Varying-Coefficient Models with Missing Response at Random |
Received:April 15, 2009 Revised:October 14, 2009 |
Key Words:
varying-coefficient model variable selection missing data.
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Fund Project:Supported by the National Natural Science Foundation of China (Grant No.10871013), the Natural Science Foundation of Beijing (Grant No.1072004), the Natural Science Foundation of Guangxi (Grant No.2010GXNSFB013051) and the Graduate Student Foundation of H |
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Abstract: |
In this paper, we present a variable selection procedure by combining basis function approximations with penalized estimating equations for varying-coefficient models with missing response at random. With appropriate selection of the tuning parameters, we establish the consistency of the variable selection procedure and the optimal convergence rate of the regularized estimators. A simulation study is undertaken to assess the finite sample performance of the proposed variable selection procedure. |
Citation: |
DOI:10.3770/j.issn:1000-341X.2011.02.008 |
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