Optimal Kernel Selection for Density Estimation

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

We provide new general kernel selection rules thanks to penalized least-squares criteria. We derive optimal oracle inequalities using adequate concentration tools. We also investigate the problem of minimal penalty as described in Birgé and Massart (2007, Probab. Theory Relat. Fields, 138(1–2):33–73).

Original languageEnglish
Title of host publicationProgress in Probability
PublisherBirkhauser
Pages425-460
Number of pages36
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes

Publication series

NameProgress in Probability
Volume71
ISSN (Print)1050-6977
ISSN (Electronic)2297-0428

Keywords

  • Density estimation
  • Kernel estimators
  • Minimal penalty
  • Optimal penalty
  • Oracle inequalities

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