Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Variance estimation in nonparametric regression with jump discontinuities

Language

English

Abstract

Variance estimation is an important topic in nonparametric regression. In this paper, we propose a pairwise regression method for estimating the residual variance. Specifically, we regress the squared difference between observations on the squared distance between design points, and then estimate the residual variance as the intercept. Unlike most existing difference-based estimators that require a smooth regression function, our method applies to regression models with jump discontinuities. Our method also applies to the situations where the design points are unequally spaced. Finally, we conduct extensive simulation studies to evaluate the finite-sample performance of the proposed method and compare it with some existing competitors. © 2013 © 2013 Taylor & Francis.

Keywords

difference-based estimator, jump point, non-uniform design, nonparametric regression, pairwise regression, residual variance

Publication Date

2014

Source Publication Title

Journal of Applied Statistics

Volume

41

Issue

3

Start Page

530

End Page

545

Publisher

Taylor & Francis

DOI

10.1080/02664763.2013.842962

ISSN (print)

02664763

ISSN (electronic)

13600532

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