Bandwidth selection for local linear regression
type: Item
instance of: scholarly article
title: Bandwidth selection for local linear regression
zbMATH Open document ID: 0938.62042
published in: Computational Statistics
publication date: 2000-05-24T00:00:00Z
review text: A new method (PURE) of bandwidth selection for nonparametric regression estimation is proposed. In PURE the bandwidth is selected as the minimizer of an estimator for mean integrated squared error (MISE). To estimate MISE the authors plug a pilot regression estimator into the bias term of the bias-variance decomposition of MISE. A minimizer of the least squares cross-validation (LSCV) score is used as a pilot estimator. The performance of PURE is compared with LSCV, direct and interactive asymptotic plug-in and global refined bandwidth selection procedures via simulation studies. The authors conclusion is that PURE selectors ``even though not always the best, compare favorably with other selectors in virtually all cases''.
Mathematics Subject Classification ID: 62G08
Mathematics Subject Classification ID: 62J02
zbMATH DE Number: 1452452
zbMATH Keywords: local linear regression
zbMATH Keywords: bandwidth selection
zbMATH Keywords: mean squared error minimization
author: Thomas C. M. Lee
author: V. Solo
MaRDI profile type: Publication
full work available at URL: s001800050029
OpenAlex ID: W1972202384
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DOI: 10.1007/S001800050029
description: scientific article; zbMATH DE number 1452452