TWO-STAGE ESTIMATION FOR SEEMINGLY UNRELATED NONPARAMETRIC REGRESSION MODELS  

作　　者：Jinhong YOU Shangyu XIE Yong ZHOU 

机构地区：[1]Department of Biostatistics, University of North Carolina at Chapel Hill Chapel Hill, NC 27599-7400, USA. [2]Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing 100080, China

出　　处：《Journal of Systems Science & Complexity》2007年第4期509-520,共12页系统科学与复杂性学报（英文版）

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.

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.

关 键 词：Asymptotic normality nonparametrie model seemingly unrelated regression two-stage estimation 

分 类 号：N94[自然科学总论—系统科学]