# mwc-probability

Sampling function-based probability distributions.

http://github.com/jtobin/mwc-probability

 Version on this page: 2.0.4@rev:1 LTS Haskell 21.24: 2.3.1 Stackage Nightly 2023-12-08: 2.3.1 Latest on Hackage: 2.3.1

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#### Module documentation for 2.0.4

• System
• System.Random
• System.Random.MWC
Depends on 4 packages(full list with versions):
Used by 7 packages in lts-12.26(full list with versions):

# mwc-probability

Sampling function-based probability distributions.

A simple probability distribution type, where distributions are characterized by sampling functions.

This implementation is a thin layer over `mwc-random`, which handles RNG state-passing automatically by using a `PrimMonad` like `IO` or `ST s` under the hood.

## Examples

• Transform a distribution’s support while leaving its density structure invariant:

``````-- uniform over [0, 1] transformed to uniform over [1, 2]
succ <\$> uniform
``````
• Sequence distributions together using bind:

``````-- a beta-binomial composite distribution
beta 1 10 >>= binomial 10
``````
• Use do-notation to build complex joint distributions from composable, local conditionals:

``````hierarchicalModel = do
[c, d, e, f] <- replicateM 4 (uniformR (1, 10))
a <- gamma c d
b <- gamma e f
p <- beta a b
n <- uniformR (5, 10)
binomial n p
``````

Check out the haddock-generated docs on Hackage for other examples.

## Etc.

PRs and issues welcome.