Package org.ojalgo.random.process
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 org.ojalgo.random.process.RandomProcess
RandomProcess.SimulationResults
-
Field Summary
Fields -
Constructor Summary
ConstructorsModifierConstructorDescriptionprivate
GaussianProcess
(GaussianField.Covariance<Double> covarFunc) GaussianProcess
(GaussianField.Mean<Double> meanFunc, GaussianField.Covariance<Double> covarFunc) -
Method Summary
Modifier and TypeMethodDescriptionvoid
(package private) double
doStep
(double stepSize, double normalisedRandomIncrement) (package private) MatrixStore
<Double> getDistribution
(double evaluationPoint) getDistribution
(Double... evaluationPoint) (package private) double
getExpected
(double stepSize) (package private) double
getLowerConfidenceQuantile
(double stepSize, double confidence) (package private) double
(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 org.ojalgo.random.process.MultipleValuesBasedProcess
addObservation, getCurrentValue, getObservations, setCurrentValue, setObservations, simulate
Methods inherited from class org.ojalgo.random.process.AbstractProcess
getExpected, getLowerConfidenceQuantile, getStandardDeviation, getUpperConfidenceQuantile, getVariance, step
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.ojalgo.random.process.RandomProcess
simulate
-
Field Details
-
GENERATOR
-
myDelegate
-
-
Constructor Details
-
GaussianProcess
-
GaussianProcess
public GaussianProcess(GaussianField.Mean<Double> meanFunc, GaussianField.Covariance<Double> covarFunc) -
GaussianProcess
private GaussianProcess()
-
-
Method Details
-
calibrate
public void calibrate() -
getDistribution
- Specified by:
getDistribution
in interfaceRandomProcess<Normal>
- Parameters:
evaluationPoint
- How far into the future?- Returns:
- The distribution for the process value at that future time.
-
getDistribution
-
getValue
public double getValue()- Specified by:
getValue
in interfaceProcess1D.ComponentProcess<Normal>
-
setValue
public void setValue(double newValue) - Specified by:
setValue
in interfaceProcess1D.ComponentProcess<Normal>
-
step
public double step(double stepSize, double standardGaussianInnovation) - Specified by:
step
in interfaceProcess1D.ComponentProcess<Normal>
-
doStep
double doStep(double stepSize, double normalisedRandomIncrement) - Specified by:
doStep
in classAbstractProcess<Normal>
-
getCovariances
MatrixStore<Double> getCovariances() -
getExpected
double getExpected(double stepSize) - Specified by:
getExpected
in classAbstractProcess<Normal>
-
getLowerConfidenceQuantile
double getLowerConfidenceQuantile(double stepSize, double confidence) - Specified by:
getLowerConfidenceQuantile
in classAbstractProcess<Normal>
-
getNormalisedRandomIncrement
double getNormalisedRandomIncrement()- Specified by:
getNormalisedRandomIncrement
in classAbstractProcess<Normal>
-
getStandardDeviation
double getStandardDeviation(double stepSize) - Specified by:
getStandardDeviation
in classAbstractProcess<Normal>
-
getUpperConfidenceQuantile
double getUpperConfidenceQuantile(double stepSize, double confidence) - Specified by:
getUpperConfidenceQuantile
in classAbstractProcess<Normal>
-
getVariance
double getVariance(double stepSize) - Specified by:
getVariance
in classAbstractProcess<Normal>
-