org.ojalgo.random.process

## Class GaussianProcess

• All Implemented Interfaces:
RandomProcess<Normal>

```public final class GaussianProcess
extends Object```
A Gaussian process is a stochastic process whose realizations consist of random values associated with every point in a range of times (or of space) such that each such random variable has a normal distribution. Moreover, every finite collection of those random variables has a multivariate normal distribution. Prior to calling getDistribution(double) or simulate(int, int, double) you must call addObservation(Double, double) one or more times.
Author:
apete

• ### Nested classes/interfaces inherited from interface org.ojalgo.random.process.RandomProcess

`RandomProcess.SimulationResults`
• ### Constructor Summary

Constructors
Constructor and Description
`GaussianProcess(GaussianField.Covariance<Double> covarFunc)`
```GaussianProcess(GaussianField.Mean<Double> meanFunc, GaussianField.Covariance<Double> covarFunc)```
• ### Constructor Detail

• #### GaussianProcess

`public GaussianProcess(GaussianField.Covariance<Double> covarFunc)`
• #### GaussianProcess

```public GaussianProcess(GaussianField.Mean<Double> meanFunc,
GaussianField.Covariance<Double> covarFunc)```
• ### Method Detail

• #### calibrate

`public void calibrate()`
• #### getDistribution

`public Normal getDistribution(double evaluationPoint)`
Parameters:
`evaluationPoint` - How far into the future?
Returns:
The distribution for the process value at that future time.
• #### getDistribution

`public Normal1D getDistribution(Double... evaluationPoint)`
• #### getNormalisedRandomIncrement

`protected double getNormalisedRandomIncrement()`
• #### step

```protected double step(double currentValue,
double stepSize,
double normalisedRandomIncrement)```

```public final boolean addObservation(Double x,
double y)```
• #### getValue

`public final double getValue()`
• #### setValue

`public final void setValue(double newValue)`
• #### simulate

```public final RandomProcess.SimulationResults simulate(int numberOfRealisations,
int numberOfSteps,
double stepSize)```
Specified by:
`simulate` in interface `RandomProcess<D extends Distribution>`
Returns:
An array of sample sets. The array has aNumberOfSteps elements, and each sample set has aNumberOfRealisations samples.
• #### setObservations

`protected final void setObservations(Collection<? extends ComparableToDouble<Double>> c)`