@hackage Dist0.5.0
A Haskell library for probability distributions
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MIT
Maintainer
will.yager@gmail.com
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Dependencies (3)
- MonadRandom >=0.5 && <0.6
- base >=4.12 && <4.13
- containers >=0.6 && <0.7 Show all…
Dependents (1)
@hackage/acme-everything
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).