On a robust local estimator for the scale function in heteroscedastic nonparametric regression

被引：8
|
作者：
Boente, Graciela [1 ,2 ]
Ruiz, Marcelo
Zamar, Ruben H. [3 ]
机构：
[1] Univ Buenos Aires, Fac Ciencias Exactas & Nat, RA-1053 Buenos Aires, DF, Argentina
[2] Consejo Nacl Invest Cient & Tecn, RA-1033 Buenos Aires, DF, Argentina
[3] Univ British Columbia, Vancouver, BC V5Z 1M9, Canada
来源：
STATISTICS & PROBABILITY LETTERS | 2010年 / 80卷 / 15-16期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Heteroscedasticity; Local M-estimators; Nonparametric regression; Robust estimation; VARIANCE-FUNCTION; KERNEL-METHOD; SELECTION; MODELS; CHOICE; SERIES;
D O I：
10.1016/j.spl.2010.03.015
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：
When the data used to fit an heteroscedastic nonparametric regression model are contaminated with outliers, robust estimators of the scale function are needed in order to obtain robust estimators of the regression function and to construct robust confidence bands. In this paper, local M-estimators of the scale function based on consecutive differences of the responses, for fixed designs are considered. Under mild regularity conditions, the asymptotic behavior of the local M-estimators for general weight functions is derived. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：1185 / 1195
页数：11
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