带有误差线性协变量的半参数变系数部分线性模型的协变量选择(英文)  

Covariate Selection for Semiparametric Varying-Coefficient Partially Linear Models with Error-Prone Linear Covariates

作　　者：周占功[1,2] 姜荣[1] 钱伟民[1] 

机构地区：[1]同济大学数学系,上海200092 [2]嘉兴学院统计系,浙江嘉兴314001

出　　处：《湘潭大学自然科学学报》2009年第4期1-6,13,共7页Natural Science Journal of Xiangtan University

基　　金：教育部高校专业设置预测系统项目

摘　　要：考虑了一些协变量不被观察到,但辅助变量可用时的半参数变系数部分线性模型.提出了基于SCAD惩罚的参数分量的变量选择方法,且估计既有渐近正态性又有先知性.模拟研究说明了所提出变量选择方法的有限样本性质.This paper considers semiparametric varying-coefficient partially linear models when some eovariates are not observed, but ancillary variables are available. A variable selection procedure for the parametric components is presented based on the SCAD penalization, and the resulting estimates perform asymptotic normality as well as an oracle property. Finite sample performance of the proposed variable selection procedures is illustrated by simulation studies.

关 键 词：辅助变量 局部线性方法 变系数模型 误差变量 SCAD 

分 类 号：O212.7[理学—概率论与数理统计]