random-fu-0.2.7.0: Random number generation
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.
Modules
- Data
- Data.Random
- Data.Random.Distribution
- Data.Random.Distribution.Bernoulli
- Data.Random.Distribution.Beta
- Data.Random.Distribution.Binomial
- Data.Random.Distribution.Categorical
- Data.Random.Distribution.ChiSquare
- Data.Random.Distribution.Dirichlet
- Data.Random.Distribution.Exponential
- Data.Random.Distribution.Gamma
- Data.Random.Distribution.Multinomial
- Data.Random.Distribution.Normal
- Data.Random.Distribution.Pareto
- Data.Random.Distribution.Poisson
- Data.Random.Distribution.Rayleigh
- Data.Random.Distribution.Simplex
- Data.Random.Distribution.StretchedExponential
- Data.Random.Distribution.T
- Data.Random.Distribution.Triangular
- Data.Random.Distribution.Uniform
- Data.Random.Distribution.Weibull
- Data.Random.Distribution.Ziggurat
- Internal
- Data.Random.Lift
- Data.Random.List
- Data.Random.RVar
- Data.Random.Sample
- Data.Random.Vector
- Data.Random.Distribution
- Data.Random