The consistency for estimator of nonparametric regression model based on NOD errors

被引：36

作者：

Yang, Wenzhi ^{[1
]}

Wang, Xuejun ^{[1
]}

Wang, Xinghui ^{[1
]}

Hu, Shuhe ^{[1
]}

机构：

[1] Anhui Univ, Sch Math Sci, Hefei 230039, Peoples R China

来源：

JOURNAL OF INEQUALITIES AND APPLICATIONS | 2012年

基金：

中国国家自然科学基金;

关键词：

NOD sequence; almost sure convergence; convergence rate; nearest; neighbor weights; FIXED-DESIGN REGRESSION; LINEAR-TIME SERIES; RANDOM-VARIABLES; EXPONENTIAL INEQUALITIES; MULTIPLE-REGRESSION; LIMIT-THEOREMS; SEQUENCE; CONVERGENCE; DEPENDENCE; SUMS;

D O I：

10.1186/1029-242X-2012-140

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

By using some inequalities for NOD random variables, we give its application to investigate the nonparametric regression model based on these errors. Some consistency results for the estimator of g(x) are presented, including the mean convergence, uniform convergence, almost sure convergence and convergence rate. We generalize some related results and as an example of designed assumptions for weight functions, we give the nearest neighbor weights. AMS Mathematical Subject Classification 2000: 62G05; 62G08.

引用

页数：13

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