Statistical Science

Density Estimation

Simon J. Sheather

Full-text: Open access

Abstract

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.

Article information

Source
Statist. Sci., Volume 19, Number 4 (2004), 588-597.

Dates
First available in Project Euclid: 18 April 2005

Permanent link to this document
https://projecteuclid.org/euclid.ss/1113832723

Digital Object Identifier
doi:10.1214/088342304000000297

Mathematical Reviews number (MathSciNet)
MR2185580

Zentralblatt MATH identifier
1100.62558

Keywords
Kernel density estimation bandwidth selection local likelihood density estimates data sharpening

Citation

Sheather, Simon J. Density Estimation. Statist. Sci. 19 (2004), no. 4, 588--597. doi:10.1214/088342304000000297. https://projecteuclid.org/euclid.ss/1113832723


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