Random-number generation based on modeling random variables as first-class entities. This library currently consists of 3 major parts:
This package defines the central datatype of the system, a monad transformer called RVarT
which extends an arbitrary monad with non-backtracking nondeterminism. In particular, the RVar
type (an alias for RVar Identity
) models pure random variables.
This package provides the backend for RVarT
; arbitrary sources of entropy. Its design is still in major flux.
This package provides an end-user interface that defines random variables following several standard distributions as well as some convenient interfaces for sampling them.
To use the system, you'll typically want import at least two modules: Data.Random
for the main interface and a supported entropy source, such as System.Random.MWC
from the mwc-random
package. You may also want to import one or more of the extra distributions provided in the Data.Random.Distribution
heirarchy (uniform and normal are exported by Data.Random
automatically). Then, you can define random variables using do
notation, sample them using sampleFrom
, etc. For example:
import Data.Random
import System.Random.MWC (create)
logNormal :: Double -> Double -> RVar Double
logNormal mu sigmaSq = do
x <- normal mu sigmaSq
return (exp x)
main = do
mwc <- create
y <- sampleFrom mwc (logNormal 5 1)
print y
Get the latest release from Hackage:
cabal install random-fu
Or a bleeding-edge version from github:
git clone https://github.com/mokus0/random-fu.git
cd random-fu
(cd random-source; cabal install)
(cd rvar; cabal install)
(cd random-fu; cabal install)