- java.lang.Object
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- org.ojalgo.random.process.AbstractProcess<D>
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- org.ojalgo.random.process.MultipleValuesBasedProcess<Normal>
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- org.ojalgo.random.process.GaussianProcess
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- All Implemented Interfaces:
Process1D.ComponentProcess<Normal>,RandomProcess<Normal>
public final class GaussianProcess extends MultipleValuesBasedProcess<Normal> implements Process1D.ComponentProcess<Normal>
A Gaussian process is aRandomProcesswhere 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.
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Nested Class Summary
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Nested classes/interfaces inherited from interface org.ojalgo.random.process.RandomProcess
RandomProcess.SimulationResults
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Field Summary
Fields Modifier and Type Field Description private static NormalGENERATORprivate GaussianField<java.lang.Double>myDelegate
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Constructor Summary
Constructors Modifier Constructor Description privateGaussianProcess()GaussianProcess(GaussianField.Covariance<java.lang.Double> covarFunc)GaussianProcess(GaussianField.Mean<java.lang.Double> meanFunc, GaussianField.Covariance<java.lang.Double> covarFunc)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description voidcalibrate()(package private) doubledoStep(double stepSize, double normalisedRandomIncrement)(package private) MatrixStore<java.lang.Double>getCovariances()NormalgetDistribution(double evaluationPoint)Normal1DgetDistribution(java.lang.Double... evaluationPoint)(package private) doublegetExpected(double stepSize)(package private) doublegetLowerConfidenceQuantile(double stepSize, double confidence)(package private) doublegetNormalisedRandomIncrement()(package private) doublegetStandardDeviation(double stepSize)(package private) doublegetUpperConfidenceQuantile(double stepSize, double confidence)doublegetValue()(package private) doublegetVariance(double stepSize)voidsetValue(double newValue)doublestep(double stepSize, double standardGaussianInnovation)-
Methods inherited from class org.ojalgo.random.process.MultipleValuesBasedProcess
addObservation, getCurrentValue, getObservations, setCurrentValue, setObservations, simulate
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Methods inherited from class org.ojalgo.random.process.AbstractProcess
getExpected, getLowerConfidenceQuantile, getStandardDeviation, getUpperConfidenceQuantile, getVariance, step
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.ojalgo.random.process.RandomProcess
simulate
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Field Detail
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GENERATOR
private static final Normal GENERATOR
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myDelegate
private final GaussianField<java.lang.Double> myDelegate
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Constructor Detail
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GaussianProcess
public GaussianProcess(GaussianField.Covariance<java.lang.Double> covarFunc)
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GaussianProcess
public GaussianProcess(GaussianField.Mean<java.lang.Double> meanFunc, GaussianField.Covariance<java.lang.Double> covarFunc)
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GaussianProcess
private GaussianProcess()
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Method Detail
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calibrate
public void calibrate()
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getDistribution
public Normal getDistribution(double evaluationPoint)
- Specified by:
getDistributionin interfaceRandomProcess<Normal>- Parameters:
evaluationPoint- How far into the future?- Returns:
- The distribution for the process value at that future time.
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getDistribution
public Normal1D getDistribution(java.lang.Double... evaluationPoint)
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getValue
public double getValue()
- Specified by:
getValuein interfaceProcess1D.ComponentProcess<Normal>
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setValue
public void setValue(double newValue)
- Specified by:
setValuein interfaceProcess1D.ComponentProcess<Normal>
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step
public double step(double stepSize, double standardGaussianInnovation)- Specified by:
stepin interfaceProcess1D.ComponentProcess<Normal>
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doStep
double doStep(double stepSize, double normalisedRandomIncrement)- Specified by:
doStepin classAbstractProcess<Normal>
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getCovariances
MatrixStore<java.lang.Double> getCovariances()
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getExpected
double getExpected(double stepSize)
- Specified by:
getExpectedin classAbstractProcess<Normal>
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getLowerConfidenceQuantile
double getLowerConfidenceQuantile(double stepSize, double confidence)- Specified by:
getLowerConfidenceQuantilein classAbstractProcess<Normal>
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getNormalisedRandomIncrement
double getNormalisedRandomIncrement()
- Specified by:
getNormalisedRandomIncrementin classAbstractProcess<Normal>
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getStandardDeviation
double getStandardDeviation(double stepSize)
- Specified by:
getStandardDeviationin classAbstractProcess<Normal>
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getUpperConfidenceQuantile
double getUpperConfidenceQuantile(double stepSize, double confidence)- Specified by:
getUpperConfidenceQuantilein classAbstractProcess<Normal>
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getVariance
double getVariance(double stepSize)
- Specified by:
getVariancein classAbstractProcess<Normal>
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