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] to uniform over [1, 2] fmap succ uniform
Sequence distributions together using bind:
-- a beta-binomial compound 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
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Downloads
- mwc-probability-2.3.1.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] | 1.0.0, 1.0.1, 1.0.2, 1.0.3, 1.1.3, 1.2.0, 1.2.1, 1.2.2, 1.3.0, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 2.2.0, 2.3.0, 2.3.1 |
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Change log | CHANGELOG |
Dependencies | base (>=4.8 && <6), containers (>=0.6), mwc-random (>0.13 && <0.16), primitive (>=0.6 && <1.0), transformers (>=0.5 && <1.0) [details] |
Tested with | ghc ==8.0.2, ghc ==8.2.2, ghc ==8.4.2, ghc ==8.6.5, ghc ==8.8.3 |
License | MIT |
Author | Jared Tobin, Marco Zocca |
Maintainer | jared@jtobin.ca, zocca.marco gmail |
Category | Math |
Home page | http://github.com/jtobin/mwc-probability |
Source repo | head: git clone http://github.com/jtobin/mwc-probability.git |
Uploaded | by JaredTobin at 2020-07-31T20:18:50Z |
Distributions | LTSHaskell:2.3.1, NixOS:2.3.1, Stackage:2.3.1 |
Reverse Dependencies | 14 direct, 3 indirect [details] |
Downloads | 12350 total (43 in the last 30 days) |
Rating | (no votes yet) [estimated by Bayesian average] |
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Status | Docs available [build log] Last success reported on 2020-07-31 [all 1 reports] |