Corrected-loss estimation for Error-in-Variable partially linear model

被引：2

作者：

Jin Jiao ^{[1
]}

Tong XingWei ^{[1
]}

机构：

[1] Beijing Normal Univ, Sch Stat, Beijing 100875, Peoples R China

来源：

SCIENCE CHINA-MATHEMATICS | 2015年 / 58卷 / 05期

基金：

中国国家自然科学基金;

关键词：

partially linear model; Error-in-Variable; robust analysis; NONPARAMETRIC REGRESSION; QUANTILE REGRESSION; ROBUST ESTIMATION;

D O I：

10.1007/s11425-015-4980-x

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We consider an Error-in-Variable partially linear model where the covariates of linear part are measured with error which follows a normal distribution with a known covariance matrix. We propose a corrected-loss estimation of the covariate effect. The proposed estimator is asymptotically normal. Simulation studies are presented to show that the proposed method performs well with finite samples, and the proposed method is applied to a real data set.

引用

页码：1101 / 1114

页数：14

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