@article{JSSv021i07, title={ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R}, volume={21}, url={https://www.jstatsoft.org/index.php/jss/article/view/v021i07}, doi={10.18637/jss.v021.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.}, number={7}, journal={Journal of Statistical Software}, author={Duong, Tarn}, year={2007}, pages={1–16} }