A NOTE ON THE CONSISTENCY OF WAVELET ESTIMATORS IN NONPARAMETRIC REGRESSION MODEL UNDER WIDELY ORTHANT DEPENDENT RANDOM ERRORS

被引：4
作者：
Ding, Liwang [1 ,2 ]
Chen, Ping [1 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Sci, Xiaolingwei St 200, Nanjing 210094, Jiangsu, Peoples R China
[2] Guangxi Univ Finance & Econ, Sch Informat & Stat, Mingxiu West Rd 100, Nanning 530003, Peoples R China
来源：
MATHEMATICA SLOVACA | 2019年 / 69卷 / 06期
基金：
美国国家科学基金会;
关键词：
widely orthant dependent; wavelet estimator; complete consistency; nonparametric regression model; RANDOM-VARIABLES; CONVERGENCE; INEQUALITY; SUMS;
D O I：
10.1515/ms-2017-0323
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
In this paper, we consider the wavelet estimators of a nonparametric regression model based on widely orthant dependent random errors. The moment consistency and the completely consistency for wavelet estimators under some more mild moment conditions are investigated. The results obtained in the paper improve and extend the corresponding ones for dependent random variables. Finally, we provide a numerical simulation to verify the validity of our results. (C) 2019 Mathematical Institute Slovak Academy of Sciences
引用
收藏
页码：1471 / 1484
页数：14
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