Empirical Likelihood Based Variable Selection for Varying Coefficient Partially Linear Models with Censored Data
Received:March 15, 2012  Revised:September 03, 2012
Key Words: varying coefficient partially linear models   empirical likelihood   censored data   variable selection.  
Fund Project:Supported by the National Natural Science Foundation of China (Grant Nos.11101119; 11126332), the National Social Science Foundation of China (Grant No.11CTJ004), the Natural Science Foundation of Guangxi Province (Grant No.2010GXNSFB013051) and the Philosophy and Social Sciences Foundation of Guangxi Province (Grant No.11FTJ002).
Author NameAffiliation
Peixi ZHAO Department of Mathematics, Hechi University, Guangxi 546300, P. R. China 
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      In this paper, we consider the variable selection for the parametric components of varying coefficient partially linear models with censored data. By constructing a penalized auxiliary vector ingeniously, we propose an empirical likelihood based variable selection procedure, and show that it is consistent and satisfies the sparsity. The simulation studies show that the proposed variable selection method is workable.
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