This Haskell library provides a number of common functions and types
useful in statistics. Our focus is on high performance, numerical
robustness, and use of good algorithms. Where possible, we provide
references to the statistical literature.

The library's facilities can be divided into three broad categories:

Working with widely used discrete and continuous probability
distributions. (There are dozens of exotic distributions in use; we
focus on the most common.)

Computing with sample data: quantile estimation, kernel density
estimation, bootstrap methods, and autocorrelation analysis.

Random variate generation under several different distributions.

Common statistical tests for significant differences between samples.

WWW:	http://darcs.serpentine.com/statistics