probability: Probabilistic Functional Programming
The Library allows exact computation with discrete random variables in terms of their distributions by using a monad. The monad is similar to the List monad for non-deterministic computations, but extends the List monad by a measure of probability. Small interface to R plotting.
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Modules
[Index] [Quick Jump]
- Numeric
- Probability
- Numeric.Probability.Distribution
- Example
- Numeric.Probability.Example.Alarm
- Numeric.Probability.Example.Barber
- Numeric.Probability.Example.Bayesian
- Numeric.Probability.Example.Boys
- Numeric.Probability.Example.Collection
- Numeric.Probability.Example.Diagnosis
- Numeric.Probability.Example.Dice
- Numeric.Probability.Example.DiceAccum
- Numeric.Probability.Example.Kruskal
- Numeric.Probability.Example.MontyHall
- Numeric.Probability.Example.NBoys
- Numeric.Probability.Example.Predator
- Numeric.Probability.Example.Profession
- Numeric.Probability.Example.Queuing
- Numeric.Probability.Example.TreeGrowth
- Numeric.Probability.Expectation
- Numeric.Probability.Object
- Numeric.Probability.Percentage
- Numeric.Probability.Random
- Numeric.Probability.Shape
- Numeric.Probability.Simulation
- Numeric.Probability.Trace
- Numeric.Probability.Transition
- Numeric.Probability.Visualize
- Probability
Flags
Automatic Flags
| Name | Description | Default |
|---|---|---|
| splitbase | Choose the new smaller, split-up base package. | Enabled |
Use -f <flag> to enable a flag, or -f -<flag> to disable that flag. More info
Downloads
- probability-0.2.8.tar.gz [browse] (Cabal source package)
- Package description (revised from the package)
Note: This package has metadata revisions in the cabal description newer than included in the tarball. To unpack the package including the revisions, use 'cabal get'.
Maintainer's Corner
For package maintainers and hackage trustees
Candidates
| Versions [RSS] | 0.1, 0.2, 0.2.1, 0.2.2, 0.2.2.1, 0.2.3, 0.2.3.1, 0.2.4, 0.2.4.1, 0.2.5, 0.2.5.1, 0.2.5.2, 0.2.6, 0.2.7, 0.2.8 |
|---|---|
| Change log | Changes.md |
| Dependencies | base (>=1.0 && <5), containers (>=0.1 && <0.9), random (>=1.0 && <1.4), special-functors (>=1.0 && <1.1), transformers (>=0.4 && <0.7), utility-ht (>=0.0.12 && <0.1) [details] |
| Tested with | ghc ==7.0.2, ghc ==7.2.2, ghc ==7.4.2, ghc ==7.8.2, ghc ==8.6.5, ghc ==8.8.3 |
| License | BSD-3-Clause |
| Author | Martin Erwig <erwig@eecs.oregonstate.edu>, Steve Kollmansberger |
| Maintainer | Henning Thielemann <haskell@henning-thielemann.de> |
| Revised | Revision 3 made by HenningThielemann at 2025年05月19日T07:25:26Z |
| Category | Math, Monads, Graphics |
| Home page | http://www.haskell.org/haskellwiki/Probabilistic_Functional_Programming |
| Source repo | head: darcs get http://code.haskell.org/~thielema/probability/ this: darcs get http://code.haskell.org/~thielema/probability/ --tag 0.2.8 |
| Uploaded | by HenningThielemann at 2023年02月15日T11:15:55Z |
| Distributions | FreeBSD:0.2.4.1, LTSHaskell:0.2.8, NixOS:0.2.8, Stackage:0.2.8 |
| Reverse Dependencies | 4 direct, 0 indirect [details] |
| Downloads | 13510 total (23 in the last 30 days) |
| Rating | (no votes yet) [estimated by Bayesian average] |
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| Status | Docs uploaded by user Build status unknown [no reports yet] |
Readme for probability-0.2.8
[back to package description]Probabilistic Functional Programming in Haskell Contact: Martin Erwig, Oregon State University, erwig@eecs.oregonstate.edu These files have been tested with GHC 6.4 Core Library files: Show.hs Pretty Printing ListUtils.hs PrintList.hs Probability.hs Core probabilistic module Visualize.hs Visualization system for use with R Examples: Barber.hs An example of the queueing system BayesianNetwork.hs Implementing Bayesian networks Boys.hs A statistical examples NBoys.hs A generalized version of the previous Collection.hs Collections and two examples: Marbles and cards Dice.hs Rolling dice MontyHall.hs The "Monty Hall" Game (statistical) Predator.hs Non-probabilistic, demonstrates visualization TreeGrowth.hs A simple tree growth example Visualize output is placed in the file FuSE.R which can be loaded into the R statistical program to see visualizations. Randomized values can be displayed to the console using the printR function, which shows the value from a IO monad function.