This library provides a number of common functions and types useful in
statistics. We focus on high performance, numerical robustness, and use of good
algorithms. Where possible, we provide references to the statistical
The library's facilities can be divided into four 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,
histograms, bootstrap methods, significance testing, and regression and
Random variate generation under several different distributions.
Common statistical tests for significant differences between samples.