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

Tarn Duong

Journal of Statistical Software, 2007, vol. 021, issue i07

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.

Date: 2007-10-16
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Citations: View citations in EconPapers (31)

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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:021:i07

DOI: 10.18637/jss.v021.i07

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