Copyright	Copyright (c) 2009-2017 David Sorokin <david.sorokin@gmail.com>
License	BSD3
Maintainer	David Sorokin <david.sorokin@gmail.com>
Stability	experimental
Safe Haskell	Safe-Inferred
Language	Haskell2010

Simulation.Aivika.Trans.Generator.Primitive

Description

Tested with: GHC 8.0.1

This helper module defines primitives for generating random numbers.

Synopsis

generateUniform01 :: Monad m => m Double -> Double -> Double -> m Double
generateUniformInt01 :: Monad m => m Double -> Int -> Int -> m Int
generateTriangular01 :: Monad m => m Double -> Double -> Double -> Double -> m Double
generateNormal01 :: Monad m => m Double -> Double -> Double -> m Double
generateLogNormal01 :: Monad m => m Double -> Double -> Double -> m Double
generateExponential01 :: Monad m => m Double -> Double -> m Double
generateErlang01 :: Monad m => m Double -> Double -> Int -> m Double
generatePoisson01 :: Monad m => m Double -> Double -> m Int
generateBinomial01 :: Monad m => m Double -> Double -> Int -> m Int
generateGamma01 :: Monad m => m Double -> m Double -> Double -> Double -> m Double
generateBeta01 :: Monad m => m Double -> m Double -> Double -> Double -> m Double
generateWeibull01 :: Monad m => m Double -> Double -> Double -> m Double
generateDiscrete01 :: Monad m => m Double -> DiscretePDF a -> m a

Documentation

generateUniform01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> Double	minimum
-> Double	maximum
-> m Double

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

generateUniformInt01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> Int	minimum
-> Int	maximum
-> m Int

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

generateTriangular01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> Double	minimum
-> Double	median
-> Double	maximum
-> m Double

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

generateNormal01 Source #

Arguments

:: Monad m
=> m Double	the normal random number ~ N (0, 1)
-> Double	mean
-> Double	variance
-> m Double

Generate a normal random number by the specified generator, mean and variance.

generateLogNormal01 Source #

Arguments

:: Monad m
=> m Double	the normal random number ~ N (0, 1)
-> Double	mean
-> Double	variance
-> m Double

Generate the lognormal random number derived from a normal distribution with the specified generator, mean and variance.

generateExponential01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> Double	the mean
-> m Double

Return the exponential random number with the specified mean.

generateErlang01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> Double	the scale
-> Int	the shape
-> m Double

Return the Erlang random number.

generatePoisson01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> Double	the mean
-> m Int

Generate the Poisson random number with the specified mean.

generateBinomial01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> Double	the probability
-> Int	the number of trials
-> m Int

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

generateGamma01 Source #

Arguments

:: Monad m
=> m Double	the normal random number ~ N (0,1)
-> m Double	the uniform random number ~ U (0, 1)
-> Double	the shape parameter (kappa)
-> Double	the scale parameter (theta)
-> m Double

Generate a random number from the Gamma distribution using Marsaglia and Tsang method.

generateBeta01 Source #

Arguments

:: Monad m
=> m Double	the normal random number ~ N (0, 1)
-> m Double	the uniform random number ~ U (0, 1)
-> Double	the shape parameter alpha
-> Double	the shape parameter beta
-> m Double

Generate a random number from the Beta distribution.

generateWeibull01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> Double	shape
-> Double	scale
-> m Double

Generate a random number from the Weibull distribution.

generateDiscrete01 Source #

Arguments

:: Monad m
=> m Double	the uniform random number ~ U (0, 1)
-> DiscretePDF a	a discrete probability density function
-> m a

Generate a random value from the specified discrete distribution.