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