Class GaussianField<K extends Comparable<? super K>>

java.lang.Object

org.ojalgo.random.process.RandomField<K>

org.ojalgo.random.process.GaussianField<K>

public final class GaussianField<K extends Comparable<? super K>>
extends RandomField<K>

This GaussianField class is a generalization, as well as the underlying implementation, of GaussianProcess. Prior to calling getDistribution(Comparable...) you must call addObservation(Comparable, double) one or more times.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static interface	GaussianField.Covariance<K extends Comparable<? super K>>
static interface	GaussianField.Mean<K extends Comparable<? super K>>

Field Summary

Fields

Modifier and Type	Field	Description
private static final PhysicalStore.Factory<Double, R064Store>	FACTORY
private GaussianField.Covariance<K>	myCovarianceFunction
private GaussianField.Mean<K>	myMeanFunction
private TreeSet<EntryPair.KeyedPrimitive<K>>	myObservations

Constructor Summary

Constructors

Constructor	Description
GaussianField(GaussianField.Covariance<K> covarFunc)
GaussianField(GaussianField.Covariance<K> covarFunc, TreeSet<EntryPair.KeyedPrimitive<K>> observations)
GaussianField(GaussianField.Mean<K> meanFunc, GaussianField.Covariance<K> covarFunc)
GaussianField(GaussianField.Mean<K> meanFunc, GaussianField.Covariance<K> covarFunc, TreeSet<EntryPair.KeyedPrimitive<K>> observations)

Method Summary

Modifier and Type	Method	Description
void	addObservation(K key, double value)
void	calibrate()
(package private) MatrixStore<Double>	getC11(K[] args)
(package private) MatrixStore<Double>	getC12(K[] args)
(package private) MatrixStore<Double>	getC21(K[] args)
(package private) MatrixDecomposition.Solver<Double>	getC22()
Normal1D	getDistribution(boolean cleanCovariances, K... evaluationPoint)
Normal1D	getDistribution(K... evaluationPoint)
(package private) MatrixStore<Double>	getM1(K[] args)
(package private) MatrixStore<Double>	getM2()
(package private) MatrixStore<Double>	getM2differenses()
(package private) List<EntryPair.KeyedPrimitive<K>>	getObservations()
(package private) MatrixStore<Double>	getRegressionCoefficients(K[] args)
private static <K extends Comparable<? super K>> GaussianField.Mean<K>	mean()

Methods inherited from class Object

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

Field Details

FACTORY

private static final PhysicalStore.Factory<Double, R064Store> FACTORY

myCovarianceFunction

private GaussianField.Covariance<K extends Comparable<? super K>> myCovarianceFunction

myMeanFunction

private GaussianField.Mean<K extends Comparable<? super K>> myMeanFunction

myObservations

private TreeSet<EntryPair.KeyedPrimitive<K extends Comparable<? super K>>> myObservations

Constructor Details

GaussianField

public GaussianField(GaussianField.Covariance<K> covarFunc)

GaussianField

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

GaussianField

GaussianField(GaussianField.Covariance<K> covarFunc,
 TreeSet<EntryPair.KeyedPrimitive<K>> observations)

GaussianField

GaussianField(GaussianField.Mean<K> meanFunc,
 GaussianField.Covariance<K> covarFunc,
 TreeSet<EntryPair.KeyedPrimitive<K>> observations)

Method Details

mean

private static <K extends Comparable<? super K>>
GaussianField.Mean<K> mean()

addObservation

public void addObservation(K key,
 double value)

calibrate

public void calibrate()

getDistribution

public Normal1D getDistribution(boolean cleanCovariances,
 K... evaluationPoint)

getDistribution

public Normal1D getDistribution(K... evaluationPoint)

getC11

MatrixStore<Double> getC11(K[] args)

getC12

MatrixStore<Double> getC12(K[] args)

getC21

MatrixStore<Double> getC21(K[] args)

getC22

MatrixDecomposition.Solver<Double> getC22()

getM1

MatrixStore<Double> getM1(K[] args)

getM2

MatrixStore<Double> getM2()

getM2differenses

MatrixStore<Double> getM2differenses()

getObservations

List<EntryPair.KeyedPrimitive<K>> getObservations()

getRegressionCoefficients

MatrixStore<Double> getRegressionCoefficients(K[] args)