Random samplers for some common distributions, based on splitmix.

Random samplers for some common distributions, as well as a convenient interface for composing them, based on splitmix. Please see the README on GitHub at https://github.com/ocramz/splitmix-distributions#readme

splitmix-distributions

Random samplers for some common distributions, as well as a convenient interface for composing them, based on splitmix.

Usage

Compose your random sampler out of simpler ones thanks to the Applicative and Monad interface, e.g. this is how you would declare and sample a binary mixture of Gaussian random variables:

import Control.Monad (replicateM)
import System.Random.SplitMix.Distributions (Gen, sample, bernoulli, normal)

process :: Gen Double
process = do
    coin <- bernoulli 0.7
    if coin
    then
        normal 0 2
    else
        normal 3 1

dataset :: [Double]
dataset = sample 1234 $ replicateM 20 process

and sample your data in a pure (sample) or monadic (sampleT) setting.

Implementation details

The library is built on top of splitmix, so the caveats on safety and performance that apply there are relevant here as well.