# normaldistribution: Minimum fuss normally distributed random values.

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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## Downloads

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

#### Maintainer's Corner

For package maintainers and hackage trustees

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Versions [RSS] | 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 | BSD-3-Clause |

Copyright | Bjorn Buckwalter 2011 |

Author | Bjorn Buckwalter |

Maintainer | bjorn.buckwalter@gmail.com |

Category | Math, Statistics |

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

Uploaded | by BjornBuckwalter at 2011-04-09T07:09:12Z |

Distributions | LTSHaskell:1.1.0.3, NixOS:1.1.0.3, Stackage:1.1.0.3 |

Reverse Dependencies | 9 direct, 2 indirect [details] |

Downloads | 9279 total (0 in the last 30 days) |

Rating | (no votes yet) [estimated by Bayesian average] |

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