probability-0.2.5.2: Probabilistic Functional Programming

Safe Haskell Safe Haskell98

Numeric.Probability.Random

Description

Randomized values

Synopsis

# random generator

newtype T a Source #

Random values

Constructors

 Cons Fieldsdecons :: State StdGen a
Instances
 Source # Instance detailsDefined in Numeric.Probability.Random Methods(>>=) :: T a -> (a -> T b) -> T b #(>>) :: T a -> T b -> T b #return :: a -> T a #fail :: String -> T a # Source # Instance detailsDefined in Numeric.Probability.Random Methodsfmap :: (a -> b) -> T a -> T b #(<\$) :: a -> T b -> T a # Source # Instance detailsDefined in Numeric.Probability.Random Methodspure :: a -> T a #(<*>) :: T (a -> b) -> T a -> T b #liftA2 :: (a -> b -> c) -> T a -> T b -> T c #(*>) :: T a -> T b -> T b #(<*) :: T a -> T b -> T a # Source # Instance detailsDefined in Numeric.Probability.Simulation Methods(~.) :: (Fractional prob, Ord prob, Random prob, Ord a) => Int -> (a -> T a) -> Transition prob a Source #(~..) :: (Fractional prob, Ord prob, Random prob, Ord a) => (Int, Int) -> (a -> T a) -> RExpand prob a Source #(~*.) :: (Fractional prob, Ord prob, Random prob, Ord a) => (Int, Int) -> (a -> T a) -> Transition prob a Source # Source # Instance detailsDefined in Numeric.Probability.Object MethodsfromFrequencies :: [(a, Double)] -> T a Source #

randomR :: Random a => (a, a) -> T a Source #

run :: T a -> IO a Source #

Run random action in IO monad.

runSeed :: StdGen -> T a -> a Source #

Run random action without IO using a seed.

print :: Show a => T a -> IO () Source #

pick :: (Num prob, Ord prob, Random prob) => T prob a -> T a Source #

# random distribution

type Distribution prob a = T (T prob a) Source #

Randomized distribution

above :: (Num prob, Ord prob, Ord a) => prob -> Distribution prob a -> Distribution prob (Select a) Source #

below :: (Num prob, Ord prob, Ord a) => prob -> Distribution prob a -> Distribution prob (Select a) Source #

dist :: (Fractional prob, Ord a) => [T a] -> Distribution prob a Source #

dist converts a list of randomly generated values into a distribution by taking equal weights for all values. Thus dist (replicate n rnd) simulates rnd n times and returns an estimation of the distribution represented by rnd.

# Randomized changes

type Change a = a -> T a Source #

random change

change :: (Num prob, Ord prob, Random prob) => T prob a -> Change a Source #

# Randomized transitions

type Transition prob a = a -> Distribution prob a Source #

random transition

type ApproxDist a = T [a] Source #