|Title:||ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R|
|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.|
Page views:: 20808. Submitted: 2007-03-04. Published: 2007-10-16.
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
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Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.