Open Access
November 2004 Density Estimation
Simon J. Sheather
Statist. Sci. 19(4): 588-597 (November 2004). DOI: 10.1214/088342304000000297

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.

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Simon J. Sheather. "Density Estimation." Statist. Sci. 19 (4) 588 - 597, November 2004. https://doi.org/10.1214/088342304000000297

Information

Published: November 2004
First available in Project Euclid: 18 April 2005

zbMATH: 1100.62558
MathSciNet: MR2185580
Digital Object Identifier: 10.1214/088342304000000297

Keywords: Bandwidth selection , data sharpening , kernel density estimation , local likelihood density estimates

Rights: Copyright © 2004 Institute of Mathematical Statistics

Vol.19 • No. 4 • November 2004
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