Estimating linear functionals of the error distribution in nonparametric regression

被引：22

作者：

Mülller, UU

Schick, A ^{[1
]}

Wefelmeyer, W

机构：

[1] Binghamton Univ, Dept Math Sci, Binghamton, NY 13902 USA

[2] Univ Bremen, Fachbereich Math & Informat 3, D-28334 Bremen, Germany

[3] Univ Siegen, Fachbereich Math 6, D-57068 Siegen, Germany

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2004年 / 119卷 / 01期

关键词：

locally polynomial smoother; nonparametric regression estimator; leave-one-out estimator; variance estimator; influence function; efficient estimator;

D O I：

10.1016/S0378-3758(02)00412-3

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：

This paper addresses estimation of linear functionals of the error distribution in nonparametric regression models. It derives an i.i.d. representation for the empirical estimator based on residuals, using undersmoothed estimators for the regression curve. Asymptotic efficiency of the estimator is proved. Estimation of the error variance is discussed in detail. In this case, undersmoothing is not necessary. (C) 2002 Elsevier B.V. All rights reserved.

引用

页码：75 / 93

页数：19

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