Robust Nonparametric Function Estimation for Errors-in-variables Models  

作　　者：Chao-xia YUAN Heng-jian CUI 

机构地区：[1]School of Mathematical Sciences,Capital Normal University,Beijing 100048,China

出　　处：《Acta Mathematicae Applicatae Sinica》2020年第2期314-331,共18页应用数学学报（英文版）

基　　金：partly supported by the National Natural Science Foundation of China(Grant Nos.1971324,11471223);Capacity Building for Sci-Tech Innovation-Fundamental Scientific Research Funds(No:19530050181);Interdiscipline for Bioinformatics and Statistics and Academy for Multidisciplinary Studies of Capital Normal University,Beijing.

摘　　要：This paper discusses robust nonparametric estimators of location regression function for errorsin-variables model with de-convolution kernel.The local constant smoother is used for the estimation of the nonparametric function,and the local linear smoother is proposed to deal with the boundary problem,as well as to improve the local constant smoother.We establish the asymptotic properties of the estimator,the influence function of the statistical functional and the breakdown point.A simulation study is carried out to demonstrate robust performance of the proposed estimator.The motorcycle data is presented to illustrate the application of the robust estimator further.

关 键 词：ERRORS-IN-VARIABLES de-convolution KERNEL ROBUST LOCAL linear 

分 类 号：O212.1[理学—概率论与数理统计]