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ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R

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Author Info
Tarn Duong
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.

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Publisher Info
Article provided by American Statistical Association in its journal Journal of Statistical Software.

Volume (Year): 21 ()
Issue (Month): i07 ()
Pages:
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Handle: RePEc:jss:jstsof:21:i07

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