Local linear estimation for regression models with locally stationary long memory errors

被引：0

作者：

Wang, Lihong ^{[1
]}

机构：

[1] Nanjing Univ, Dept Math, Nanjing 210093, Jiangsu, Peoples R China

来源：

JOURNAL OF THE KOREAN STATISTICAL SOCIETY | 2016年 / 45卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Asymptotic behavior; Local linear regression estimation; Locally stationary long memory process; DEPENDENT ERRORS; RANGE DEPENDENCE;

D O I：

10.1016/j.jkss.2015.12.005

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 consider the local linear regression estimation for the nonparametric regression models with locally stationary long memory errors. The asymptotic behaviors of the regression estimators are established. It is shown that there is a multiple bandwidth dichotomy for the asymptotic distribution of the estimators of the regression function and its derivatives. The finite sample performance of the estimator is discussed through simulation studies. (C) 2016 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

引用

页码：381 / 394

页数：14

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