Simulation.Aivika.Trans.Generator

Tested with: GHC 8.0.1

Below is defined a random number generator.

Documentation

class (Functor m, Monad m) => MonadGenerator m where

Defines a monad whithin which computation the random number generator can work.

Minimal complete definition

generateUniform, generateUniformInt, generateTriangular, generateNormal, generateLogNormal, generateExponential, generateErlang, generatePoisson, generateBinomial, generateGamma, generateBeta, generateWeibull, generateDiscrete, generateSequenceNo, newGenerator, newRandomGenerator, newRandomGenerator01

Associated Types

data Generator m :: *

Defines a random number generator.

Methods

generateUniform :: Generator m -> Double -> Double -> m Double

Generate an uniform random number with the specified minimum and maximum.

generateUniformInt :: Generator m -> Int -> Int -> m Int

Generate an uniform integer random number with the specified minimum and maximum.

generateTriangular :: Generator m -> Double -> Double -> Double -> m Double

Generate a triangular random number by the specified minimum, median and maximum.

generateNormal :: Generator m -> Double -> Double -> m Double

Generate a normal random number with the specified mean and deviation.

generateLogNormal :: Generator m -> Double -> Double -> m Double

Generate a random number from the lognormal distribution derived from a normal distribution with the specified mean and deviation.

generateExponential :: Generator m -> Double -> m Double

Generate a random number distributed exponentially with the specified mean (the reciprocal of the rate).

generateErlang :: Generator m -> Double -> Int -> m Double

Generate the Erlang random number with the specified scale (the reciprocal of the rate) and integer shape.

generatePoisson :: Generator m -> Double -> m Int

Generate the Poisson random number with the specified mean.

generateBinomial :: Generator m -> Double -> Int -> m Int

Generate the binomial random number with the specified probability and number of trials.

generateGamma :: Generator m -> Double -> Double -> m Double

Generate a random number from the Gamma distribution with the specified shape (kappa) and scale (theta, a reciprocal of the rate).

The probability density for the Gamma distribution is

f x = x ** (kappa - 1) * exp (- x / theta) / theta ** kappa * Gamma kappa

generateBeta :: Generator m -> Double -> Double -> m Double

Generate a random number from the Beta distribution by the specified shape parameters (alpha and beta).

The probability density for the Beta distribution is

f x = x ** (alpha - 1) * (1 - x) ** (beta - 1) / B alpha beta

generateWeibull :: Generator m -> Double -> Double -> m Double

Generate a random number from the Weibull distribution by the specified shape and scale.

generateDiscrete :: forall a. Generator m -> DiscretePDF a -> m a

Generate a random value from the specified discrete distribution.

generateSequenceNo :: Generator m -> m Int

Generate a sequence number which can be considered quite unique.

newGenerator :: GeneratorType m -> m (Generator m)

Create a new random number generator.

newRandomGenerator :: RandomGen g => g -> m (Generator m)

Create a new random generator by the specified standard generator.

newRandomGenerator01 :: m Double -> m (Generator m)

Create a new random generator by the specified uniform generator of numbers from 0 to 1.

data GeneratorType m

Defines a type of the random number generator.

Constructors

SimpleGenerator

The simple random number generator.

SimpleGeneratorWithSeed Int

The simple random number generator with the specified seed.

CustomGenerator (m (Generator m))

The custom random number generator.

CustomGenerator01 (m Double)

The custom random number generator by the specified uniform generator of numbers from 0 to 1.

type DiscretePDF a = [(a, Double)]

A discrete probability density function.