Some uniform convergence results for kernel estimators  

作　　者：MENG MeiXia AI ChunRong 

机构地区：[1]School of Statistics and Management,Shanghai University of Finance and Economics [2]School of Statistics and Management,Key Laboratory of Mathematical Economics,Ministry of Education,Shanghai University of Finance and Economics [3]Department of Economics,University of Florida

出　　处：《Science China Mathematics》2013年第9期1945-1956,共12页中国科学：数学（英文版）

基　　金：National Natural Science Foundation of China (Grant No. 70971082);Shanghai Leading Academic Discipline Project at Shanghai University of Finance and Economics (SHUFE) (Grant No. B803);Key Laboratory of Mathematical Economics (SHUFE), Ministry of Education

摘　　要：This paper derives some uniform convergence rates for kernel regression of some index functions that may depend on infinite dimensional parameter. The rates of convergence are computed for independent, strongly mixing and weakly dependent data respectively. These results extend the existing literature and are useful for the derivation of large sample properties of the estimators in some semiparametric and nonparametric models.This paper derives some uniform convergence rates for kernel regression of some index functions that may depend on infinite dimensional parameter. The rates of convergence are computed for independent, strongly mixing and weakly dependent data respectively. These results extend the existing literature and are useful for the derivation of large sample properties of the estimators in some semiparametric and nonparametric models.

关 键 词：uniform convergence kernel estimation convergence rate 

分 类 号：G210[文化科学—新闻学]