randproc: Data structures and support functions for working with random processes

[ bsd3, data-structures, library ] [ Propose Tags ] [ Report a vulnerability ]

RandProc.hs - a Haskell library for working with random processes in a mathematically rigorous way (Concepts taken from Random Processes - a Mathematical Approach for Engineers by: - Robert M. Gray - Lee D. Davisson Prentice-Hall Information and System Sciences Series, Thomas Kailath, Series Editor)

[Skip to Readme]

Modules

[Index]

Data
- Data.RandProc

Downloads

randproc-0.4.tar.gz [browse] (Cabal source package)
Package description (as included in the package)

Maintainer's Corner

Package maintainers

DavidBanas

For package maintainers and hackage trustees

edit package information

Candidates

No Candidates

Versions [RSS]	0.1, 0.2, 0.3, 0.4
Dependencies	base (>=3 && <5) [details]
License	BSD-3-Clause
Author	David Banas
Maintainer	dbanas@banasfamily.net
Category	Data Structures
Home page	http://www.haskell.org/haskellwiki/Random_Processes
Bug tracker	http://trac.haskell.org/RandProc/
Uploaded	by DavidBanas at 2011-07-03T14:57:29Z
Distributions	NixOS:0.4
Reverse Dependencies	1 direct, 0 indirect [details]
Downloads	3305 total (6 in the last 30 days)
Rating	(no votes yet) [estimated by Bayesian average]
Your Rating	λ λ λ
Status	Docs uploaded by user Build status unknown [no reports yet]

Readme for randproc-0.4

[back to package description]

This is the `RandProc` library, written by David Banas.

For more info, please, see the comments in `Data/RandProc.hs`.
Alternatively, view the Haddock generated HTML documentation:
  $ cabal haddock

For information on the community support infrastructure for this library,
view the home page for this library:
  http://www.haskell.org/haskellwiki/Random_Processes
There you will find links to:
- mailing list
- blog
- bug tracker
- etc.

For usage examples, please, see:
- test/Test.hs
    Darcs check-in tests
- Data/RandProc/Examples/Problems/*.hs
    example problems, taken from the text upon which this library is based

The intent of this library is to provide the data structures and support
functions necessary for working with abstract probability spaces, in a
mathematically rigorous way. It is not intended to provide functionality for
generating distributions, moments, expectations, etc., as there are already
libraries available for this. (`Probabilistic Functional Programming` is one
that I've seen, but haven't had a chance to investigate, yet.)