probability: Probabilistic Functional Programming

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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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Versions0.1, 0.2, 0.2.1, 0.2.2,, 0.2.3,, 0.2.4,, 0.2.5,,,
Change logNone available
Dependenciesbase (>=1.0 && <5), containers (>=0.1 && <0.7), random (>=1.0 && <2), special-functors (==1.0.*), transformers (>=0.0.1 && <0.6), utility-ht (>=0.0.6 && <0.1) [details]
AuthorMartin Erwig <>, Steve Kollmansberger
MaintainerHenning Thielemann <>
CategoryMath, Monads, Graphics
Home page
Source repositoryhead: darcs clone
this: darcs clone --tag
UploadedSat Sep 1 10:48:04 UTC 2018 by HenningThielemann





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Probabilistic Functional Programming in Haskell

Martin Erwig, Oregon State University,

These files have been tested with GHC 6.4

Core Library files:

Show.hs		Pretty Printing
Probability.hs	Core probabilistic module
Visualize.hs	Visualization system for use with R


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.