Module ojalgo

Package org.ojalgo.random.process

Interface RandomProcess<D extends Distribution>

All Known Implementing Classes:

GaussianProcess, GeometricBrownianMotion, PoissonProcess, StationaryNormalProcess, WienerProcess

public interface RandomProcess<D extends Distribution>

A random/stochastic process (a series of random variables indexed by time or space) representing the evolution of some random value. The key thing you can do with a random process is to ask for its distribution at a given (future) time.

Author:

apete

Nested Class Summary

Nested Classes

Modifier and Type	Interface	Description
static final class	RandomProcess.SimulationResults

Method Summary

Modifier and Type	Method	Description
D	getDistribution(double evaluationPoint)
RandomProcess.SimulationResults	simulate(int numberOfRealisations, int numberOfSteps, double stepSize)	Returns an collection of sample sets.

Method Details

getDistribution

D getDistribution(double evaluationPoint)

Parameters:

evaluationPoint - How far into the future?

Returns:

The distribution for the process value at that future time.

simulate

RandomProcess.SimulationResults simulate(int numberOfRealisations,
 int numberOfSteps,
 double stepSize)

Returns an collection of sample sets. The array has numberOfSteps elements, and each sample set has numberOfRealisations samples.