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randproc: Data structures and support functions for working with random processes
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randproc: Data structures and support functions for working with random processes
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)
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Downloads
- randproc-0.4.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] | 0.1, 0.2, 0.3, 0.4 |
|---|---|
| Dependencies | base (>=3 && <5) [details] |
| License | BSD-3-Clause |
| Author | David Banas |
| Maintainer | dbanas@banasfamily.net |
| Uploaded | by DavidBanas at 2011-07-03T14:57:29Z |
| Category | Data Structures |
| Home page | https://www.haskell.org/haskellwiki/Random_Processes |
| Bug tracker | https://trac.haskell.org/RandProc/ |
| Distributions | NixOS:0.4 |
| Reverse Dependencies | 1 direct, 0 indirect [details] |
| Downloads | 3387 total (14 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 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:
https://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.)