Simulation.Aivika.Net.Random

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.

Documentation

randomUniformNet

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

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.

randomTriangularNet

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.

randomNormalNet

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.

randomLogNormalNet

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.

randomExponentialNet

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

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

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

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.

randomGammaNet

Arguments

:: Double

the shape

-> Double

the scale (a reciprocal of the rate)

-> Net a a

When processing every input element, hold the process for a random time interval having the Gamma distribution with the specified shape and scale.

randomBetaNet

Arguments

:: Double

shape (alpha)

-> Double

shape (beta)

-> Net a a

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).

randomWeibullNet

Arguments

:: Double

shape

-> Double

scale

-> Net a a

When processing every input element, hold the process for a random time interval having the Weibull distribution with the specified shape and scale.

randomDiscreteNet

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.