Dist: A Haskell library for probability distributions

[ library, math, mit ] [ Propose Tags ]

This library provides a data structure and associated functions for representing discrete probability distributions.


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Versions [faq] 0.1.0.0, 0.2.0.0, 0.3.0.0, 0.4.0.0, 0.4.1.0, 0.4.2, 0.5.0
Dependencies base (==4.12.*), containers (==0.6.*), MonadRandom (==0.5.*) [details]
License MIT
Author William Yager
Maintainer will.yager@gmail.com
Category Math
Home page https://github.com/wyager/Dist
Source repo head: git clone https://github.com/wyager/Dist.git
Uploaded by wyager at Sun Jun 16 09:28:45 UTC 2019
Distributions NixOS:0.5.0
Downloads 2205 total (149 in the last 30 days)
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Status Hackage Matrix CI
Docs available [build log]
Last success reported on 2019-06-16 [all 1 reports]

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Dist

A Haskell library for probability distributions

This library provides a data structure and associated functions for representing discrete probability distributions.

This library is optimized for very fast sampling. If n is the number of unique outcomes, sampling from the distribution is O(log(n)) worst case, and O(1) best case.

The average time complexity depends on the distribution. A more evenly distributed distribution will be closer to O(log(n)). A less evenly dsitributed distribution will be closer to O(1).