# The normaldistribution package

This purpose of this library is to have a simple API and no
dependencies beyond Haskell 98 in order to let you produce
normally distributed random values with a minimum of fuss. This
library does *not* attempt to be blazingly fast nor to pass
stringent tests of randomness. It attempts to be very easy to
install and use while being "good enough" for many applications
(simulations, games, etc.). The API builds upon and is largely
analogous to that of the Haskell 98 `Random` module (more
recently `System.Random`).

Pure:

(sample,g) = normal myRandomGen -- using a Random.RandomGen samples = normals myRandomGen -- infinite list samples2 = mkNormals 10831452 -- infinite list using a seed

In the IO monad:

sample <- normalIO samples <- normalsIO -- infinite list

With custom mean and standard deviation:

(sample,g) = normal' (mean,sigma) myRandomGen samples = normals' (mean,sigma) myRandomGen samples2 = mkNormals' (mean,sigma) 10831452

sample <- normalIO' (mean,sigma) samples <- normalsIO' (mean,sigma)

Internally the library uses the Central Limit Theorem to approximate normally distributed values from multiple uniformly distributed random values.

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## Properties

Versions | 1.0, 1.1, 1.1.0.1, 1.1.0.2, 1.1.0.3 |
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Dependencies | base (<5), haskell98 (<1.1) [details] |

License | BSD3 |

Copyright | Bjorn Buckwalter 2011 |

Author | Bjorn Buckwalter |

Maintainer | bjorn.buckwalter@gmail.com |

Stability | Stable |

Category | Math, Statistics |

Home page | https://github.com/bjornbm/normaldistribution |

Uploaded | Sat Apr 9 07:09:12 UTC 2011 by BjornBuckwalter |

Distributions | NixOS:1.1.0.3 |

Downloads | 3809 total (7 in the last 30 days) |

Votes | |

Status | Docs not available [build log] All reported builds failed as of 2016-12-28 [all 7 reports] |

## Modules

*Data**Random*- Data.Random.Normal

## Downloads

- normaldistribution-1.0.tar.gz [browse] (Cabal source package)
- Package description (included in the package)