Limit behaviors of regression function estimator with martingale difference errors

被引：0
|
作者：
Liu, Chang [1 ]
Li, Zhen [1 ]
Miao, Yu [1 ,2 ]
机构：
[1] Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Henan, Peoples R China
[2] Henan Normal Univ, Henan Engn Lab Big Data Stat Anal & Optimal Contr, Xinxiang, Henan, Peoples R China
来源：
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2022年
基金：
中国国家自然科学基金;
关键词：
Martingale difference; Moment convergency; Nonparametric regression model strong consistency; The estimator of Priestley and Chao; NONPARAMETRIC FUNCTION ESTIMATION; FIXED-DESIGN REGRESSION; TIME-SERIES; DENSITY-FUNCTION; INEQUALITIES; CONSISTENCY; SEQUENCES;
D O I：
10.1080/03610918.2022.2142241
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 the present paper, we consider the nonparametric regression model Y-i = g(x(i)) + epsilon(i), 1 <= i <= n, and study the strong consistency and uniform strong consistency of the estimator of Priestley and Chao based on the martingale difference errors. These results partially extend and improve some known works. Furthermore, the moment convergency and uniform moment convergency of the estimator are established also.
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页数：15
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