On the consistency of the P-C estimator in a nonparametric regression model

被引：7

作者：

Wu, Yi ^{[1
]}

Wang, Xuejun ^{[1
]}

Balakrishnan, Narayanaswamy ^{[2
]}

机构：

[1] Anhui Univ, Sch Math Sci, Hefei 230601, Peoples R China

[2] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada

来源：

STATISTICAL PAPERS | 2020年 / 61卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Extended negatively dependent random variables; P-C estimator; Nonparametric regression; Convergence rate; Consistency; PRECISE LARGE DEVIATIONS; RANDOM-VARIABLES; COMPLETE CONVERGENCE;

D O I：

10.1007/s00362-017-0966-9

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, we investigate the nonparametric regression model based on extended negatively dependent errors. Some consistency results for the estimator of the regression function g(x) are presented, including the rates of strong consistency and complete consistency, and the mean convergence. The results obtained in this paper improve and extend the corresponding ones of Yang and Wang (Acta Math Appl Sin 22(4):522-530, 1999) and Priestley and Chao (J R Stat Soc B 34:385-392, 1972). Finally, we present a numerical simulation study to verify the validity of the results established here.

引用

页码：899 / 915

页数：17

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