Article thumbnail

Uniform in bandwidth consistency of kernel-type function estimators

By Uwe Einmahl and David M. Mason

Abstract

We introduce a general method to prove uniform in bandwidth consistency of kernel-type function estimators. Examples include the kernel density estimator, the Nadaraya–Watson regression estimator and the conditional empirical process. Our results may be useful to establish uniform consistency of data-driven bandwidth kernel-type function estimators. 1. Introduction and statements of main results. Let X,X1,X2,... be i.i.d. Rd, d ≥ 1, valued random variables and assume that the common distribution function of these variables has a Lebesgue density function, which we shall denote by f. A kernel K will be any measurable function whic

Year: 2005
DOI identifier: 10.1214/009053605000000129
OAI identifier: oai:CiteSeerX.psu:10.1.1.238.381
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://arxiv.org/pdf/math/0507... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.