Variable Selection in the Partially Linear Errors-in-Variables Models for Longitudinal Data  

作　　者：Yi-ping YANG Liu-gen XUE Wei-hu CHENG 

机构地区：[1]College of Mathematics and Statistics,Chongqing Technology and Business University [2]Department of Applied Mathematics,Beijing University of Technology

出　　处：《Acta Mathematicae Applicatae Sinica》2012年第4期769-780,共12页应用数学学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China (Nos.11126332 and 11101452);the National Social Science Foundation of China (No.11CTJ004);the Natural Science Foundation Project of CQ CSTC(No.cstc2011jjA00014);the Research Foundation of Chongqing Municipal Education Commission (No.KJ110720)

摘　　要：This paper proposes a new approach for variable selection in partially linear errors-in-variables （EV） models for longitudinal data by penalizing appropriate estimating functions. We apply the SCAD penalty to simultaneously select significant variables and estimate unknown parameters. The rate of convergence and the asymptotic normality of the resulting estimators are established. Furthermore, with proper choice of regularization parameters, we show that the proposed estimators perform as well as the oracle procedure. A new algorithm is proposed for solving penalized estimating equation. The asymptotic results are augmented by a simulation study.This paper proposes a new approach for variable selection in partially linear errors-in-variables （EV） models for longitudinal data by penalizing appropriate estimating functions. We apply the SCAD penalty to simultaneously select significant variables and estimate unknown parameters. The rate of convergence and the asymptotic normality of the resulting estimators are established. Furthermore, with proper choice of regularization parameters, we show that the proposed estimators perform as well as the oracle procedure. A new algorithm is proposed for solving penalized estimating equation. The asymptotic results are augmented by a simulation study.

关 键 词：ERRORS-IN-VARIABLES variable selection estimating function ORACLE SCAD 

分 类 号：O212.1[理学—概率论与数理统计]