Shape-restricted nonparametric regression with overall noisy measurements

被引：4

作者：

Pflug, Georg Ch ^{[1
,2
]}

Wets, Roger J. -B. ^{[3
]}

机构：

[1] Univ Vienna, Dept Stat, A-1010 Vienna, Austria

[2] IIASA, Laxenburg, Austria

[3] Univ Calif Davis, Dept Math, Davis, CA 95616 USA

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2013年 / 25卷 / 02期

关键词：

nonparametric regression; error in variables; graph topology; constrained maximum likelihood; shape restrictions; 62G08; 62G20; DENSITY;

D O I：

10.1080/10485252.2012.754890

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：

For a nonparametric regression problem with errors in variables, we consider a shape-restricted regression function estimate, which does not require the choice of bandwidth parameters. We demonstrate that this estimate is consistent for classes of regression function candidates, which are closed under the graph topology.

引用

页码：323 / 338

页数：16

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