TWO-STAGE ESTIMATION FOR SEEMINGLY UNRELATED NONPARAMETRIC REGRESSION MODELS

作     者：Jinhong YOU Shangyu XIE Yong ZHOU 

作者机构：Department of Biostatistics University of North Carolina at Chapel Hill Chapel Hill NC 27599-7400 USA. Institute of Applied Mathematics Chinese Academy of Sciences Beijing 100080 China 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2007年第20卷第4期

页      面：509-520页

核心收录：

学科分类：0711[理学-系统科学] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 08[工学] 0811[工学-控制科学与工程] 081103[工学-系统工程] 

基　　金：The research was supported in part by National Natural Science Foundation of China (NSFC) under Grants No. 10471140 and No. 10731010  the National Basic Research Program of China (973 Program) under Grant No. 2007CB814902  and Science Fund for Creative Research Groups 

主　　题：Asymptotic normality nonparametrie model seemingly unrelated regression two-stage estimation 

摘      要：This paper is concerned with the estimating problem of seemingly unrelated （SU） non- parametric regression models. The authors propose a new method to estimate the unknown functions, which is an extension of the two-stage procedure in the longitudinal data framework. The authors show the resulted estimators are asymptotically normal and more efficient than those based on only the individual regression equation. Some simulation studies are given in support of the asymptotic results. A real data from an ongoing environmental epidemiologie study are used to illustrate the proposed procedure.