Density estimation

Research output: Contribution to journalArticlepeer-review

450 Scopus citations


This paper provides a practical description of density estimation based on kernel methods. An important aim is to encourage practicing statisticians to apply these methods to data. As such, reference is made to implementations of these methods in R, S-PLUS and SAS.

Original languageEnglish
Pages (from-to)588-597
Number of pages10
JournalStatistical Science
Issue number4
StatePublished - Nov 2004


  • Bandwidth selection
  • Data sharpening
  • Kernel density estimation
  • Local likelihood density estimates

ASJC Scopus subject areas

  • Statistics and Probability
  • General Mathematics
  • Statistics, Probability and Uncertainty


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