Averaged singular integral estimation as a bias reduction technique

被引：1

作者：

Delgado, MA ^{[1
]}

Vidal-Sanz, JM

机构：

[1] Univ Carlos III Madrid, Madrid, Spain

[2] London Sch Econ, London, England

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2002年 / 80卷 / 01期

关键词：

global rates of convergence for the bias; singular integral estimators; bias reduction techniques; generalized jackknife;

D O I：

10.1006/jmva.2000.1978

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 proposes an averaged version of singular integral estimators, whose bias achieves higher rates of convergence under smoothing assumptions. We derive exact bias bounds, without imposing smoothing assumptions, which are a basis for deriving the rates of convergence tinder differentiability assumptions. (C) 2001 Elsevier Science.

引用

页码：127 / 137

页数：11

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