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Authors: Tarn Duong
Title: [download]
(14390)
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
Reference: Vol. 21, Issue 7, Oct 2007
Submitted 2007-03-04, Accepted 2007-09-12
Type: Article
Abstract:

Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing. Currently it contains functionality for kernel density estimation and kernel discriminant analysis. It is a comprehensive package for bandwidth matrix selection, implementing a wide range of data-driven diagonal and unconstrained bandwidth selectors.

Paper: [download]
(14390)
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
(application/pdf, 1003.7 KB)
Supplements: [download]
(1351)
ks_1.5.2.tar.gz: R source package
(application/x-gzip, 270 KB)
[download]
(1262)
v21i07.R: R example code from the paper
(application/zip, 646 Bytes)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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