rvar: Random Variables
Random number generation based on modeling random
variables by an abstract type (
RVar) which can be
composed and manipulated monadically and sampled in
either monadic or "pure" styles.
The primary purpose of this library is to support defining and sampling a wide variety of high quality random variables. Quality is prioritized over speed, but performance is an important goal too.
In my testing, I have found it capable of speed comparable to other Haskell libraries, but still a fair bit slower than straight C implementations of the same algorithms.
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mtl-2 has State, etc., as "type" rather than "newtype"
Use -f <flag> to enable a flag, or -f -<flag> to disable that flag. More info
- rvar-0.3.0.1.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
For package maintainers and hackage trustees
|Versions [RSS]||0.2, 0.2.0.1, 0.2.0.2, 0.2.0.3, 0.2.0.4, 0.2.0.6, 0.3.0.0, 0.3.0.1|
|Dependencies||base (>=3 && <5), bytestring, MonadPrompt (>=1.0 && <1.1), mtl (>=1.1 && <1.2 || >=2 && <3), random (>=1.2.0), transformers (>=0.2 && <0.6) [details]|
|Author||James Cook <email@example.com>|
|Maintainer||Dominic Steinitz <firstname.lastname@example.org>|
|Source repo||head: git clone https://github.com/haskell-numerics/random-fu(rvar)|
|Uploaded||by DominicSteinitz at 2022-05-22T08:17:59Z|
|Distributions||Arch:0.3.0.1, Debian:0.2.0.6, LTSHaskell:0.3.0.1, NixOS:0.3.0.1, Stackage:0.3.0.1|
|Reverse Dependencies||11 direct, 55 indirect [details]|
|Downloads||11198 total (45 in the last 30 days)|
|Rating||(no votes yet) [estimated by Bayesian average]|
|Status||Docs available [build log]
Last success reported on 2022-05-22 [all 1 reports]