Package0.3.0.1Math
random-fu
Random number generation
- Version0.3.0.1
- CategoryMath
- LicenceLicenseRef-PublicDomain
- AuthorJames Cook <mokus@deepbondi.net>
- MaintainerDominic Steinitz <dominic@steinitz.org>
- Homepagegithub.com/mokus0/random-fu
- Pinned byhackage random-fu 0.3.0.1
- Sourcehackage.haskell.org/package/random-fu-0.3.0.1
Modules
29 modules- Data.Random32Flexible modeling and sampling of random variables. The central abstraction in this library is the concept of a random
- Data.Random.Distribution3
- Data.Random.Distribution.Bernoulli7
- Data.Random.Distribution.Beta5
- Data.Random.Distribution.Binomial11
- Data.Random.Distribution.Categorical15
- Data.Random.Distribution.ChiSquare3
- Data.Random.Distribution.Dirichlet4
- Data.Random.Distribution.Exponential5
- Data.Random.Distribution.Gamma7
- Data.Random.Distribution.Multinomial3
- Data.Random.Distribution.Normal12
- Data.Random.Distribution.Pareto3
- Data.Random.Distribution.Poisson9
- Data.Random.Distribution.Rayleigh5
- Data.Random.Distribution.Simplex4
- Data.Random.Distribution.StretchedExponential5
- Data.Random.Distribution.T3
- Data.Random.Distribution.Triangular3
- Data.Random.Distribution.Uniform24
- Data.Random.Distribution.Weibull1
- Data.Random.Distribution.Ziggurat6A generic "ziggurat algorithm" implementation. Fairly rough right
- Data.Random.Lift1
- Data.Random.List8
- Data.Random.RVar8
- Data.Random.Sample4
- Data.Random.Vector1
Internal modules · 2
Description
Random number generation based on modeling random variables in two complementary ways: first, by the parameters of standard mathematical distributions and, second, 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.
Depends on
12 packages- base-4.20.2.0with GHC
- erf-2.0.0.0in this set
- math-functions-0.3.4.4in this set
- monad-loops-0.4.3in this set
- mtl-2.3.1with GHC
- random-1.2.1.3in this set
- random-shuffle-0.0.4in this set
- rvar-0.3.0.2in this set
- syb-0.7.3in this set
- template-haskell-2.22.0.0with GHC
- transformers-0.6.1.1with GHC
- vector-0.13.2.0in this set
Used by in this set · 0
Nothing in this set depends on it.