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For statistical analysis, the most complete computing environment available is the R programming language. R started as GNU freeware alternative to the proprietary Splus. In some senses, due to the massive contributions from the statistical research community, it has become a better product than the latter.

My main software product is the

ks (kernel smoothing)

package which implements a wide range of multivariate kernel smoothers (e.g. density estimation, density derivative estimation, classification, clustering, regression etc.), as well as sophisticated visualisation graphics. I started writing it as a doctoral candidate in the early 2000s, and I've carefully nurtured it into its present form with a certain maturity. This package is released under the General Public Licence (GPL >= 2) so anyone is free to download and use from the CRAN (Comprehensive R Archive Network), along with hundreds of other user-contribted extension libraries to the base R distribution. It also forms the basis for the practical data analysis exposited in the book Multivariate Kernel Smoothing and Its Applications.

Other sofware I've developed in R include:

A partial measure of the usage of the CRAN packages can be gleaned from the download statistics from the RStudio CRAN mirror:

Current version Last 30 days Since Oct 2012
ks
feature
prim