Local M-estimator for nonparametric time series

被引：39

作者：

Cai, ZW ^{[1
]}

Ould-Saïd, E

机构：

[1] Univ N Carolina, Dept Math, Charlotte, NC 28223 USA

[2] Univ Littoral Cote Opale, LMPA J Liouville, F-62228 Calais, France

来源：

STATISTICS & PROBABILITY LETTERS | 2003年 / 65卷 / 04期

关键词：

alpha-mixing; asymptotic properties; local smoothers; outlier; robustness; variable bandwidth;

D O I：

10.1016/j.spl.2003.08.008

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 article, we investigate a robust version of local linear regression smoothers for stationary time series sequence by using robust-type local polynomial techniques. Under some regularity conditions, we establish the weak and strong consistency as well as the asymptotic normality of the proposed estimators. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：433 / 449

页数：17

共 44 条

[1]

AUESTAD B, 1990, BIOMETRIKA, V77, P669, DOI 10.2307/2337091

[2] ASYMPTOTIC-DISTRIBUTION OF ROBUST ESTIMATORS FOR NONPARAMETRIC MODELS FROM MIXING PROCESSES [J].