org.ojalgo.random.process
Class WienerProcess

java.lang.Object
  org.ojalgo.random.process.WienerProcess

All Implemented Interfaces:

RandomProcess<Normal>

public final class WienerProcess
extends Object

Constructor Summary

WienerProcess()

Method Summary

Normal	getDistribution(double aStepSize) Calling this method repeatedly gives the same ressult, unless you call RandomProcess.step(double) inbetween.
double	getExpected(double aStepSize)
double	getLowerConfidenceQuantile(double aStepSize, double aConfidence)
double	getStandardDeviation(double aStepSize)
double	getUpperConfidenceQuantile(double aStepSize, double aConfidence)
double	getValue()
double	getVariance(double aStepSize)
void	setValue(double newValue)
SampleSet[]	simulate(int aNumberOfRealisations, int aNumberOfSteps, double aStepSize)
double	step(double aStepSize) Calling this method repeatedly gives different, random, ressults.

Methods inherited from class java.lang.Object

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

Constructor Detail

WienerProcess

public WienerProcess()

Method Detail

getDistribution

public Normal getDistribution(double aStepSize)

Description copied from interface: RandomProcess

Calling this method repeatedly gives the same ressult, unless you call RandomProcess.step(double) inbetween.

Parameters:

aStepSize - How far into the future?

Returns:

The distribution for the process value at that future time.

getExpected

public double getExpected(double aStepSize)

getLowerConfidenceQuantile

public double getLowerConfidenceQuantile(double aStepSize,
                                         double aConfidence)

getStandardDeviation

public double getStandardDeviation(double aStepSize)

getUpperConfidenceQuantile

public double getUpperConfidenceQuantile(double aStepSize,
                                         double aConfidence)

getVariance

public double getVariance(double aStepSize)

getValue

public final double getValue()

setValue

public final void setValue(double newValue)

simulate

public final SampleSet[] simulate(int aNumberOfRealisations,
                                  int aNumberOfSteps,
                                  double aStepSize)

Specified by:

simulate in interface RandomProcess<D extends ContinuousDistribution>

Returns:

An array of sample sets. The array has aNumberOfSteps elements, and each sample set has aNumberOfRealisations samples.

step

public final double step(double aStepSize)

Description copied from interface: RandomProcess

Calling this method repeatedly gives different, random, ressults. Further, calling this method should update the process state so that subsequent calls to getDistribution would be different.

Specified by:

step in interface RandomProcess<D extends ContinuousDistribution>

Parameters:

aStepSize - How far into the future?

Returns:

The new (randomly generated) process value at that future time.