aivika-5.3.1: A multi-method simulation library

Simulation.Aivika.Dynamics.Random

Description

Tested with: GHC 8.0.1

This module defines the random functions that always return the same values in the integration time points within a single simulation run. The values for another simulation run will be regenerated anew.

For example, the computations returned by these functions can be used in the equations of System Dynamics.

Also it is worth noting that the values are generated in a strong order starting from starttime with step dt. This is how the memo0Dynamics function actually works.

Synopsis

# Documentation

Arguments

 :: Dynamics Double minimum -> Dynamics Double maximum -> Simulation (Dynamics Double)

Computation that generates random numbers distributed uniformly and memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Int minimum -> Dynamics Int maximum -> Simulation (Dynamics Int)

Computation that generates random integer numbers distributed uniformly and memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double minimum -> Dynamics Double median -> Dynamics Double maximum -> Simulation (Dynamics Double)

Computation that generates random numbers from the triangular distribution and memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double mean -> Dynamics Double deviation -> Simulation (Dynamics Double)

Computation that generates random numbers distributed normally and memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double the mean of a normal distribution which this distribution is derived from -> Dynamics Double the deviation of a normal distribution which this distribution is derived from -> Simulation (Dynamics Double)

Computation that generates random numbers from the lognormal distribution and memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double the mean (a reciprocal of the rate) -> Simulation (Dynamics Double)

Computation that generates exponential random numbers with the specified mean (the reciprocal of the rate) and memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double the scale (a reciprocal of the rate) -> Dynamics Int the shape -> Simulation (Dynamics Double)

Computation that generates the Erlang random numbers with the specified scale (the reciprocal of the rate) and integer shape but memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double the mean -> Simulation (Dynamics Int)

Computation that generats the Poisson random numbers with the specified mean and memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double the probability -> Dynamics Int the number of trials -> Simulation (Dynamics Int)

Computation that generates binomial random numbers with the specified probability and trials but memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double shape -> Dynamics Double scale (a reciprocal of the rate) -> Simulation (Dynamics Double)

Computation that generates random numbers from the Gamma distribution with the specified shape and scale but memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double shape (alpha) -> Dynamics Double shape (beta) -> Simulation (Dynamics Double)

Computation that generates random numbers from the Beta distribution by the specified shape parameters and memoizes the numbers in the integration time points.

Arguments

 :: Dynamics Double shape -> Dynamics Double scale -> Simulation (Dynamics Double)

Computation that generates random numbers from the Weibull distribution with the specified shape and scale but memoizes the numbers in the integration time points.

Computation that generates random values from the specified discrete distribution and memoizes the values in the integration time points.