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Non-parametric estimation of residual moments and covariance

Jones, Antonia Jane and Evans, Dafydd 2008. Non-parametric estimation of residual moments and covariance. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 464 (2099) , pp. 2831-2846. 10.1098/rspa.2007.0195

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Abstract

The aim of non-parametric regression is to model the behaviour of a response vector Y in terms of an explanatory vector X, based only on a finite set of empirical observations. This is usually performed under the additive hypothesis Y=f(X)+R, where f(X)=(Y|X) is the true regression function and R is the true residual variable. Subject to a Lipschitz condition on f, we propose new estimators for the moments (scalar response) and covariance (vector response) of the residual distribution, derive their asymptotic properties and discuss their application in practical data analysis.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Mathematics
Subjects: Q Science > QA Mathematics
Uncontrolled Keywords: non-parametric regression; exploratory data analysis; difference-based methods; nearest neighbours
Publisher: Royal Society
ISSN: 1364-5021
Last Modified: 04 Jun 2017 02:57
URI: http://orca-mwe.cf.ac.uk/id/eprint/14278

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