The statistics package

[Tags: bsd3, library]

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 literature.

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

Changes in 0.10.4.0

Changes in 0.10.3.0

Changes in 0.10.2.0

Changes in 0.10.1.0


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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, 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
Change logChangeLog
Dependenciesbase (>=4.6 && <5), binary (>=0.6.3.0), deepseq (>=1.1.0.2), erf, math-functions (>=0.1.2), monad-par (>=0.3.4), mwc-random (>=0.11.0.0), primitive (>=0.3), vector (>=0.7.1), vector-algorithms (>=0.4), vector-binary-instances (>=0.2.1) [details]
LicenseBSD3
Copyright2009, 2010, 2011 Bryan O'Sullivan
AuthorBryan O'Sullivan <bos@serpentine.com>
MaintainerBryan O'Sullivan <bos@serpentine.com>
CategoryMath, Statistics
Home pagehttps://github.com/bos/statistics
Bug trackerhttps://github.com/bos/statistics/issues
Source repositoryhead: git clone https://github.com/bos/statistics
head: hg clone https://bitbucket.org/bos/statistics
UploadedWed May 1 19:58:32 UTC 2013 by BryanOSullivan
UpdatedMon Jan 5 22:23:08 UTC 2015 by HerbertValerioRiedel to revision 1
DistributionsDebian:0.13.2.3, FreeBSD:0.13.2.3, LTSHaskell:0.13.2.3, NixOS:0.13.2.3, Stackage:0.13.2.3
Downloads24447 total (767 in last 30 days)
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StatusDocs uploaded by user
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For package maintainers and hackage trustees

Readme for statistics-0.10.4.0

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.

Performance

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 optimisation.

Get involved!

Please report bugs via the github issue tracker.

Master git mirror:

There's also a Mercurial mirror:

(You can create and contribute changes using either Mercurial or git.)

Authors

This library is written and maintained by Bryan O'Sullivan, bos@serpentine.com.