Class GaussianProcess

java.lang.Object

org.ojalgo.random.process.AbstractProcess<Normal>

org.ojalgo.random.process.MultipleValuesBasedProcess<Normal>

org.ojalgo.random.process.GaussianProcess

All Implemented Interfaces:

Process1D.ComponentProcess<Normal>, RandomProcess<Normal>

public final class GaussianProcess
extends MultipleValuesBasedProcess<Normal>
implements Process1D.ComponentProcess<Normal>

A Gaussian process is a RandomProcess where each variable has a normal distribution. In addition, every finite collection of those variables has a multivariate normal distribution.

Prior to calling getDistribution(double) or MultipleValuesBasedProcess.simulate(int, int, double) you must call MultipleValuesBasedProcess.addObservation(Double, double) one or more times.

Nested Class Summary

Nested classes/interfaces inherited from interface RandomProcess

RandomProcess.SimulationResults

Field Summary

Fields

Modifier and Type	Field	Description
private static final Normal	GENERATOR
private final GaussianField<Double>	myDelegate

Constructor Summary

Constructors

Modifier	Constructor	Description
private	GaussianProcess()
	GaussianProcess(GaussianField.Covariance<Double> covarFunc)
	GaussianProcess(GaussianField.Mean<Double> meanFunc, GaussianField.Covariance<Double> covarFunc)

Method Summary

Modifier and Type	Method	Description
void	calibrate()
(package private) double	doStep(double stepSize, double normalisedRandomIncrement)
(package private) MatrixStore<Double>	getCovariances()
Normal	getDistribution(double evaluationPoint)
Normal1D	getDistribution(Double... evaluationPoint)
(package private) double	getExpected(double stepSize)
(package private) double	getLowerConfidenceQuantile(double stepSize, double confidence)
(package private) double	getNormalisedRandomIncrement()
(package private) double	getStandardDeviation(double stepSize)
(package private) double	getUpperConfidenceQuantile(double stepSize, double confidence)
double	getValue()
(package private) double	getVariance(double stepSize)
void	setValue(double newValue)
double	step(double stepSize, double standardGaussianInnovation)

Methods inherited from class MultipleValuesBasedProcess

addObservation, getCurrentValue, getObservations, setCurrentValue, setObservations, simulate

Methods inherited from class AbstractProcess

getExpected, getLowerConfidenceQuantile, getStandardDeviation, getUpperConfidenceQuantile, getVariance, step

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface RandomProcess

simulate

Field Details

GENERATOR

private static final Normal GENERATOR

myDelegate

private final GaussianField<Double> myDelegate

Constructor Details

GaussianProcess

public GaussianProcess(GaussianField.Covariance<Double> covarFunc)

GaussianProcess

public GaussianProcess(GaussianField.Mean<Double> meanFunc,
 GaussianField.Covariance<Double> covarFunc)

GaussianProcess

private GaussianProcess()

Method Details

calibrate

public void calibrate()

getDistribution

public Normal getDistribution(double evaluationPoint)

Specified by:

getDistribution in interface RandomProcess<Normal>

Parameters:

evaluationPoint - How far into the future?

Returns:

The distribution for the process value at that future time.

getDistribution

public Normal1D getDistribution(Double... evaluationPoint)

getValue

public double getValue()

Specified by:

getValue in interface Process1D.ComponentProcess<Normal>

setValue

public void setValue(double newValue)

Specified by:

setValue in interface Process1D.ComponentProcess<Normal>

step

public double step(double stepSize,
 double standardGaussianInnovation)

Specified by:

step in interface Process1D.ComponentProcess<Normal>

doStep

double doStep(double stepSize,
 double normalisedRandomIncrement)

Specified by:

doStep in class AbstractProcess<Normal>

getCovariances

MatrixStore<Double> getCovariances()

getExpected

double getExpected(double stepSize)

Specified by:

getExpected in class AbstractProcess<Normal>

getLowerConfidenceQuantile

double getLowerConfidenceQuantile(double stepSize,
 double confidence)

Specified by:

getLowerConfidenceQuantile in class AbstractProcess<Normal>

getNormalisedRandomIncrement

double getNormalisedRandomIncrement()

Specified by:

getNormalisedRandomIncrement in class AbstractProcess<Normal>

getStandardDeviation

double getStandardDeviation(double stepSize)

Specified by:

getStandardDeviation in class AbstractProcess<Normal>

getUpperConfidenceQuantile

double getUpperConfidenceQuantile(double stepSize,
 double confidence)

Specified by:

getUpperConfidenceQuantile in class AbstractProcess<Normal>

getVariance

double getVariance(double stepSize)

Specified by:

getVariance in class AbstractProcess<Normal>