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

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

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 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, bootstrap methods, signigicance testing, and autocorrelation analysis.

Random variate generation under several different distributions.

Common statistical tests for significant differences between samples.


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Modules

[Last Documentation]

  • Statistics
    • Statistics.Autocorrelation
    • Statistics.Constants
    • Statistics.Distribution
      • Statistics.Distribution.Beta
      • Statistics.Distribution.Binomial
      • Statistics.Distribution.ChiSquared
      • Statistics.Distribution.Exponential
      • Statistics.Distribution.Gamma
      • Statistics.Distribution.Geometric
      • Statistics.Distribution.Hypergeometric
      • Statistics.Distribution.LogNormal
      • Statistics.Distribution.Normal
      • Statistics.Distribution.Poisson
      • Statistics.Distribution.Triangular
    • Statistics.Function
    • Statistics.KernelDensity
    • Statistics.Math
    • Statistics.Quantile
    • Statistics.Resampling
      • Statistics.Resampling.Bootstrap
    • Statistics.Sample
      • Statistics.Sample.Powers
    • Test
      • Statistics.Test.NonParametric
    • 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, mwc-random (>=0.7.0.0), primitive (>=0.3), time, vector (>=0.6.0.2), vector-algorithms (>=0.3.2 && <0.4) [details]
License BSD-3-Clause
Copyright 2009, 2010 Bryan O'Sullivan
Author Bryan O'Sullivan <bos@serpentine.com>
Maintainer Bryan O'Sullivan <bos@serpentine.com>
Revised Revision 1 made by HerbertValerioRiedel at 2015-01-10T21:22:02Z
Category Math, Statistics
Home page http://bitbucket.org/bos/statistics
Bug tracker http://bitbucket.org/bos/statistics/issues
Source repo head: hg clone http://bitbucket.org/bos/statistics
Uploaded by BryanOSullivan at 2010-10-10T15:14:50Z
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, 3566 indirect [details]
Downloads 115546 total (445 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 2016-12-12 [all 7 reports]

Readme for statistics-0.8.0.2

[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.


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.

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:

http://bitbucket.org/bos/statistics


Authors
-------

Bryan O'Sullivan <bos@serpentine.com>