Title

Optimal zone for bandwidth selection in semiparametric models

Publication Type

Journal Article

Publication Date

9-2011

Abstract

We study the general problem of bandwidth selection in semiparametric regression. By expanding the higher-order terms in the Taylor series for the asymptotic mean-squared error, we provide a theoretical justification for the earlier empirical observations of an optimal zone of bandwidths in the literature. Based on the idea of cross-validating parametrical estimates, we further introduce a novel bandwidth selector for semiparametric models. The method is demonstrated by numerical studies to be able to preserve the selected bandwidth within the optimal zone. This data-driven cross-validation method may also be applicable for model diagnosis and longitudinal data settings. Examples from two clinical trials are provided to illustrate the applications.

Keywords

optimal bandwidth, cross-validation, asymptotic mean square error, Taylor series expansion, Neumann series approximation

Discipline

Statistical Theory | Statistics and Probability

Research Areas

Economic Theory

Publication

Journal of Nonparametric Statistics

Volume

23

Issue

3

First Page

701

Last Page

717

ISSN

1048-5252

Identifier

10.1080/10485252.2010.533768

Publisher

American Statistical Association

Additional URL

http://doi.org./10.1080/10485252.2010.533768

This document is currently not available here.

Share

COinS