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 |
Tested with: GHC 8.0.1
This module defines some useful random processors that hold the current process for the corresponding time interval, when processing every input element.
Synopsis
- randomUniformProcessor :: Double -> Double -> Processor a a
- randomUniformIntProcessor :: Int -> Int -> Processor a a
- randomTriangularProcessor :: Double -> Double -> Double -> Processor a a
- randomNormalProcessor :: Double -> Double -> Processor a a
- randomLogNormalProcessor :: Double -> Double -> Processor a a
- randomExponentialProcessor :: Double -> Processor a a
- randomErlangProcessor :: Double -> Int -> Processor a a
- randomPoissonProcessor :: Double -> Processor a a
- randomBinomialProcessor :: Double -> Int -> Processor a a
- randomGammaProcessor :: Double -> Double -> Processor a a
- randomBetaProcessor :: Double -> Double -> Processor a a
- randomWeibullProcessor :: Double -> Double -> Processor a a
- randomDiscreteProcessor :: DiscretePDF Double -> Processor a a
Documentation
randomUniformProcessor Source #
When processing every input element, hold the process for a random time interval distributed uniformly.
randomUniformIntProcessor Source #
When processing every input element, hold the process for a random time interval distributed uniformly.
randomTriangularProcessor Source #
:: Double | the minimum time interval |
-> Double | the median of the time interval |
-> Double | the maximum time interval |
-> Processor a a |
When processing every input element, hold the process for a random time interval having the triangular distribution.
randomNormalProcessor Source #
When processing every input element, hold the process for a random time interval distributed normally.
randomLogNormalProcessor Source #
:: Double | the mean for a normal distribution which this distribution is derived from |
-> Double | the deviation for a normal distribution which this distribution is derived from |
-> Processor a a |
When processing every input element, hold the process for a random time interval having the lognormal distribution.
randomExponentialProcessor Source #
When processing every input element, hold the process for a random time interval distributed exponentially with the specified mean (the reciprocal of the rate).
randomErlangProcessor Source #
When processing every input element, hold the process for a random time interval having the Erlang distribution with the specified scale (the reciprocal of the rate) and shape parameters.
randomPoissonProcessor Source #
When processing every input element, hold the process for a random time interval having the Poisson distribution with the specified mean.
randomBinomialProcessor Source #
When processing every input element, hold the process for a random time interval having the binomial distribution with the specified probability and trials.
When processing every input element, hold the process for a random time interval having the Gamma distribution with the specified shape and scale.
When processing every input element, hold the process for a random time interval having the Beta distribution with the specified shape parameters (alpha and beta).
randomWeibullProcessor Source #
When processing every input element, hold the process for a random time interval having the Weibull distribution with the specified shape and scale.
randomDiscreteProcessor Source #
:: DiscretePDF Double | the discrete probability density function |
-> Processor a a |
When processing every input element, hold the process for a random time interval having the specified discrete distribution.