Safe Haskell | Safe |
---|---|

Language | Haskell98 |

Randomized values

## Synopsis

- newtype T a = Cons {}
- randomR :: Random a => (a, a) -> T a
- run :: T a -> IO a
- runSeed :: StdGen -> T a -> a
- print :: Show a => T a -> IO ()
- pick :: (Num prob, Ord prob, Random prob) => T prob a -> T a
- type Distribution prob a = T (T prob a)
- above :: (Num prob, Ord prob, Ord a) => prob -> Distribution prob a -> Distribution prob (Select a)
- below :: (Num prob, Ord prob, Ord a) => prob -> Distribution prob a -> Distribution prob (Select a)
- dist :: (Fractional prob, Ord a) => [T a] -> Distribution prob a
- type Change a = a -> T a
- change :: (Num prob, Ord prob, Random prob) => T prob a -> Change a
- type Transition prob a = a -> Distribution prob a
- type ApproxDist a = T [a]

# random generator

Random values

## Instances

Monad T Source # | |

Functor T Source # | |

Applicative T Source # | |

C T Source # | |

Defined in Numeric.Probability.Simulation (~.) :: (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 # | |

C Double T Source # | |

Defined in Numeric.Probability.Object fromFrequencies :: [(a, Double)] -> 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

# Randomized transitions

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

random transition

type ApproxDist a = T [a] Source #