| 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.Net.Random
Description
Tested with: GHC 8.0.1
This module defines some useful random network computations that hold the current process for the corresponding time interval, when processing every input element.
Synopsis
- randomUniformNet :: Double -> Double -> Net a a
- randomUniformIntNet :: Int -> Int -> Net a a
- randomTriangularNet :: Double -> Double -> Double -> Net a a
- randomNormalNet :: Double -> Double -> Net a a
- randomLogNormalNet :: Double -> Double -> Net a a
- randomExponentialNet :: Double -> Net a a
- randomErlangNet :: Double -> Int -> Net a a
- randomPoissonNet :: Double -> Net a a
- randomBinomialNet :: Double -> Int -> Net a a
- randomGammaNet :: Double -> Double -> Net a a
- randomBetaNet :: Double -> Double -> Net a a
- randomWeibullNet :: Double -> Double -> Net a a
- randomDiscreteNet :: DiscretePDF Double -> Net a a
Documentation
When processing every input element, hold the process for a random time interval distributed uniformly.
When processing every input element, hold the process for a random time interval distributed uniformly.
Arguments
| :: Double | the minimum time interval |
| -> Double | the median of the time interval |
| -> Double | the maximum time interval |
| -> Net a a |
When processing every input element, hold the process for a random time interval having the triangular distribution.
When processing every input element, hold the process for a random time interval distributed normally.
Arguments
| :: Double | the mean of a normal distribution which this distribution is derived from |
| -> Double | the deviation of a normal distribution which this distribution is derived from |
| -> Net a a |
When processing every input element, hold the process for a random time interval having the lognormal distribution.
When processing every input element, hold the process for a random time interval distributed exponentially with the specified mean (the reciprocal of the rate).
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.
When processing every input element, hold the process for a random time interval having the Poisson distribution with the specified mean.
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).
When processing every input element, hold the process for a random time interval having the Weibull distribution with the specified shape and scale.
Arguments
| :: DiscretePDF Double | the discrete probability density function |
| -> Net a a |
When processing every input element, hold the process for a random time interval having the specified discrete distribution.