Simulation.Aivika.Trans.Parameter.Random

Tested with: GHC 8.0.1

This module defines the random parameters of simulation experiments.

To create a parameter that would return the same value within the simulation run, you should memoize the computation with help of memoParameter, which is important for the Monte-Carlo simulation.

To create a random function that would return the same values in the integration time points within the simulation run, you should either lift the computation to the Dynamics computation and then memoize it too but using the memo0Dynamics function for that computation, or just take the predefined function that does namely this.

Documentation

randomUniform

Arguments

:: MonadComp m

=> Double

minimum

-> Double

maximum

-> Parameter m Double

Computation that generates a new random number distributed uniformly.

randomUniformInt

Arguments

:: MonadComp m

=> Int

minimum

-> Int

maximum

-> Parameter m Int

Computation that generates a new random integer number distributed uniformly.

randomTriangular

Arguments

:: MonadComp m

=> Double

minimum

-> Double

median

-> Double

maximum

-> Parameter m Double

Computation that generates a new random number from the triangular distribution.

randomNormal

Arguments

:: MonadComp m

=> Double

mean

-> Double

deviation

-> Parameter m Double

Computation that generates a new random number distributed normally.

randomLogNormal

Arguments

:: MonadComp m

=> 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

-> Parameter m Double

Computation that generates a new random number from the lognormal distribution.

randomExponential

Arguments

:: MonadComp m

=> Double

the mean (the reciprocal of the rate)

-> Parameter m Double

Computation that returns a new exponential random number with the specified mean (the reciprocal of the rate).

randomErlang

Arguments

:: MonadComp m

=> Double

the scale (the reciprocal of the rate)

-> Int

the shape

-> Parameter m Double

Computation that returns a new Erlang random number with the specified scale (the reciprocal of the rate) and integer shape.

randomPoisson

Arguments

:: MonadComp m

=> Double

the mean

-> Parameter m Int

Computation that returns a new Poisson random number with the specified mean.

randomBinomial

Arguments

:: MonadComp m

=> Double

the probability

-> Int

the number of trials

-> Parameter m Int

Computation that returns a new binomial random number with the specified probability and trials.

randomGamma

Arguments

:: MonadComp m

=> Double

the shape

-> Double

the scale (a reciprocal of the rate)

-> Parameter m Double

Computation that returns a new random number from the Gamma distribution.

randomBeta

Arguments

:: MonadComp m

=> Double

the shape (alpha)

-> Double

the shape (beta)

-> Parameter m Double

Computation that returns a new random number from the Beta distribution.

randomWeibull

Arguments

:: MonadComp m

=> Double

shape

-> Double

scale

-> Parameter m Double

Computation that returns a new random number from the Weibull distribution.

randomDiscrete :: MonadComp m => DiscretePDF a -> Parameter m a

Computation that returns a new random value from the specified discrete distribution.

randomTrue

Arguments

:: MonadComp m

=> Double

the probability of the success

-> Parameter m Bool

Computation that returns True in case of success.

randomFalse

Arguments

:: MonadComp m

=> Double

the probability of the success

-> Parameter m Bool

Computation that returns False in case of success.