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statistics: A library of statistical types, data, and functions.

[ bsd2, library, math, statistics ] [ Propose Tags ]

A library of statistical types, data, and functions.

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  • Statistics
    • Statistics.Distribution
      • Statistics.Distribution.Normal
    • Statistics.Function
    • Statistics.KernelDensity
    • Statistics.Quantile
    • Statistics.Sample
    • Statistics.Types

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Versions [RSS] 0.1, 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, 0.5.0.0, 0.5.1.0, 0.5.1.1, 0.5.1.2, 0.6.0.0, 0.6.0.1, 0.6.0.2, 0.7.0.0, 0.8.0.0, 0.8.0.1, 0.8.0.2, 0.8.0.3, 0.8.0.4, 0.8.0.5, 0.9.0.0, 0.10.0.0, 0.10.0.1, 0.10.1.0, 0.10.2.0, 0.10.3.0, 0.10.3.1, 0.10.4.0, 0.10.4.1, 0.10.5.0, 0.10.5.1, 0.10.5.2, 0.11.0.0, 0.11.0.1, 0.11.0.2, 0.11.0.3, 0.12.0.0, 0.13.1.0, 0.13.1.1, 0.13.2.0, 0.13.2.1, 0.13.2.2, 0.13.2.3, 0.13.3.0, 0.14.0.0, 0.14.0.1, 0.14.0.2, 0.15.0.0, 0.15.1.0, 0.15.1.1, 0.15.2.0, 0.16.0.0, 0.16.0.1, 0.16.0.2, 0.16.1.0, 0.16.1.1, 0.16.1.2, 0.16.2.0, 0.16.2.1 (info)
Dependencies base (<5), erf, uvector (>=0.1.0.4), uvector-algorithms [details]
License BSD-3-Clause
Copyright 2009 Bryan O'Sullivan
Author Bryan O'Sullivan <bos@serpentine.com>
Maintainer Bryan O'Sullivan <bos@serpentine.com>
Category Math, Statistics
Home page http://darcs.serpentine.com/statistics
Uploaded by BryanOSullivan at 2009-09-08T07:23:20Z
Distributions Arch:0.16.2.1, Debian:0.15.2.0, Fedora:0.16.2.0, FreeBSD:0.13.2.3, LTSHaskell:0.16.2.1, NixOS:0.16.2.1, Stackage:0.16.2.1, openSUSE:0.16.2.1
Reverse Dependencies 64 direct, 3573 indirect [details]
Downloads 116138 total (441 in the last 30 days)
Rating 2.25 (votes: 2) [estimated by Bayesian average]
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Status Docs not available [build log]
All reported builds failed as of 2016-12-31 [all 7 reports]

Readme for statistics-0.1

[back to package description] 
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.


Source code
-----------

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


Authors
-------

Bryan O'Sullivan <bos@serpentine.com>