A brief survey of bandwidth selection for density estimation

M. C. Jones, J. S. Marron, S. J. Sheather

Research output: Contribution to journalArticlepeer-review

888 Scopus citations

Abstract

There has been major progress in recent years in data-based bandwidth selection for kernel density estimation. Some “second generation” methods, including plug-in and smoothed bootstrap techniques, have been developed that are far superior to well-known “first generation” methods, such as rules of thumb, least squares cross-validation, and biased cross-validation. We recommend a “solve-the-equation” plug-in bandwidth selector as being most reliable in terms of overall performance. This article is intended to provide easy accessibility to the main ideas for nonexperts.

Original languageEnglish
Pages (from-to)401-407
Number of pages7
JournalJournal of the American Statistical Association
Volume91
Issue number433
DOIs
StatePublished - Mar 1 1996

Keywords

  • Bandwidth selection
  • Kernel density estimation
  • Nonparametric curve estimation
  • Smoothing parameter selection

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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