The statistics package

[Tags: bsd3, library]

This 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.

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Versions0.1, 0.2, 0.2.1, 0.2.2, 0.3, 0.3.1, 0.3.2, 0.3.3, 0.3.4, 0.3.5, 0.3.6, 0.4.0, 0.4.1,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
Change logNone available
Dependenciesbase (<5), erf, mwc-random (>=, primitive, time, vector (>=0.5), vector-algorithms (==0.3.*) [details]
Copyright2009, 2010 Bryan O'Sullivan
AuthorBryan O'Sullivan <>
MaintainerBryan O'Sullivan <>
CategoryMath, Statistics
Home page
UploadedSun Jul 4 20:10:27 UTC 2010 by BryanOSullivan
UpdatedSat Jan 10 21:24:56 UTC 2015 by HerbertValerioRiedel to revision 1
DistributionsDebian:, FreeBSD:, LTSHaskell:, NixOS:, Stackage:
Downloads25163 total (577 in last 30 days)
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StatusDocs uploaded by user
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Maintainers' corner

For package maintainers and hackage trustees

Readme for statistics-

Statistics: efficient, general purpose statistics

This package provides the Statistics module, a Haskell library for
working with statistical data in a space- and time-efficient way.

Where possible, we give citations and computational complexity
estimates for the algorithms used.


This library has been carefully optimised for high performance.  To
obtain the best runtime efficiency, it is imperative to compile
libraries and applications that use this library using a high level of

Suggested GHC options:

  -O -fvia-C -funbox-strict-fields

To illustrate, here are the times (in seconds) to generate and sum 250
million random Word32 values, on a laptop with a 2.4GHz Core2 Duo
P8600 processor, running Fedora 11 and GHC 6.10.3:

  no flags   200+
  -O           1.249
  -O -fvia-C   0.991

As the numbers above suggest, compiling without optimisation will
yield unacceptable performance.

Get involved!

Please feel welcome to contribute new code or bug fixes.  You can
fetch the source repository from here:

darcs get


Bryan O'Sullivan <>