aivika-4.0.1: A multi-paradigm simulation library

CopyrightCopyright (c) 2009-2015, David Sorokin <david.sorokin@gmail.com>
LicenseBSD3
MaintainerDavid Sorokin <david.sorokin@gmail.com>
Stabilityexperimental
Safe HaskellNone
LanguageHaskell2010

Simulation.Aivika.Net.Random

Description

Tested with: GHC 7.8.3

This module defines some useful random network computations that hold the current process for the corresponding time interval, when processing every input element.

Synopsis

Documentation

randomUniformNet Source

Arguments

:: Double

the minimum time interval

-> Double

the maximum time interval

-> Net a a 

When processing every input element, hold the process for a random time interval distributed uniformly.

randomUniformIntNet Source

Arguments

:: Int

the minimum time interval

-> Int

the maximum time interval

-> Net a a 

When processing every input element, hold the process for a random time interval distributed uniformly.

randomNormalNet Source

Arguments

:: Double

the mean time interval

-> Double

the time interval deviation

-> Net a a 

When processing every input element, hold the process for a random time interval distributed normally.

randomExponentialNet Source

Arguments

:: Double

the mean time interval (the reciprocal of the rate)

-> Net a a 

When processing every input element, hold the process for a random time interval distributed exponentially with the specified mean (the reciprocal of the rate).

randomErlangNet Source

Arguments

:: Double

the scale (the reciprocal of the rate)

-> Int

the shape

-> Net a a 

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.

randomPoissonNet Source

Arguments

:: Double

the mean time interval

-> Net a a 

When processing every input element, hold the process for a random time interval having the Poisson distribution with the specified mean.

randomBinomialNet Source

Arguments

:: Double

the probability

-> Int

the number of trials

-> Net a a 

When processing every input element, hold the process for a random time interval having the binomial distribution with the specified probability and trials.