Package Info

ghc-mwc-probability


Sampling function-based probability distributions


Development/Libraries/Haskell

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] to uniform over [1, 2] > succ <$> uniform

Sequence distributions together using bind:

> -- a beta-binomial conjugate 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.


License: MIT
URL: https://hackage.haskell.org/package/mwc-probability

Categories

Releases

Package Version Update ID Released Package Hub Version Platforms Subpackages
1.3.0-bp150.2.3 info GA Release 2018-08-01 15
  • AArch64
  • ghc-mwc-probability
  • ghc-mwc-probability-devel
1.3.0-bp150.2.6 info GA Release 2018-07-30 15
  • x86-64
  • ghc-mwc-probability
  • ghc-mwc-probability-devel
1.3.0-bp150.2.8 info GA Release 2018-07-31 15
  • ppc64le
  • ghc-mwc-probability
  • ghc-mwc-probability-devel