RandomProcess

All Known Subinterfaces:

Process1D.ComponentProcess<D>

All Known Implementing Classes:

AbstractProcess, GaussianProcess, GeometricBrownianMotion, MultipleValuesBasedProcess, PoissonProcess, SingleValueBasedProcess, 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.

Nested Class Summary

Nested Classes
Modifier and Type Interface Description

static class RandomProcess.SimulationResults

Method Summary

All Methods Instance Methods Abstract Methods
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 Detail
  - 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.