Package org.ojalgo.random.process
Class AbstractProcess<D extends Distribution>
- java.lang.Object
-
- org.ojalgo.random.process.AbstractProcess<D>
-
- All Implemented Interfaces:
RandomProcess<D>
- Direct Known Subclasses:
MultipleValuesBasedProcess
,SingleValueBasedProcess
abstract class AbstractProcess<D extends Distribution> extends java.lang.Object implements RandomProcess<D>
-
-
Nested Class Summary
-
Nested classes/interfaces inherited from interface org.ojalgo.random.process.RandomProcess
RandomProcess.SimulationResults
-
-
Constructor Summary
Constructors Constructor Description AbstractProcess()
-
Method Summary
All Methods Instance Methods Abstract Methods Concrete Methods Modifier and Type Method Description (package private) abstract double
doStep(double stepSize, double normalisedRandomIncrement)
(package private) abstract double
getCurrentValue()
double
getExpected()
Equivalent to callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenDistribution.getExpected()
.(package private) abstract double
getExpected(double stepSize)
double
getLowerConfidenceQuantile(double confidence)
The same thing can be achieved by first callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenContinuousDistribution.getQuantile(double)
(but with different input argument).(package private) abstract double
getLowerConfidenceQuantile(double stepSize, double confidence)
(package private) abstract double
getNormalisedRandomIncrement()
double
getStandardDeviation()
Equivalent to callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenDistribution.getStandardDeviation()
.(package private) abstract double
getStandardDeviation(double stepSize)
double
getUpperConfidenceQuantile(double confidence)
The same thing can be achieved by first callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenContinuousDistribution.getQuantile(double)
(but with different input argument).(package private) abstract double
getUpperConfidenceQuantile(double stepSize, double confidence)
double
getVariance()
Equivalent to callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenDistribution.getVariance()
.(package private) abstract double
getVariance(double stepSize)
(package private) abstract void
setCurrentValue(double currentValue)
(package private) double
step(double stepSize)
-
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
getDistribution, simulate
-
-
-
-
Method Detail
-
getExpected
public final double getExpected()
Equivalent to callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenDistribution.getExpected()
.
-
getLowerConfidenceQuantile
public final double getLowerConfidenceQuantile(double confidence)
The same thing can be achieved by first callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenContinuousDistribution.getQuantile(double)
(but with different input argument).
-
getStandardDeviation
public final double getStandardDeviation()
Equivalent to callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenDistribution.getStandardDeviation()
.
-
getUpperConfidenceQuantile
public final double getUpperConfidenceQuantile(double confidence)
The same thing can be achieved by first callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenContinuousDistribution.getQuantile(double)
(but with different input argument).
-
getVariance
public final double getVariance()
Equivalent to callingRandomProcess.getDistribution(double)
with argumant1.0
, and thenDistribution.getVariance()
.
-
doStep
abstract double doStep(double stepSize, double normalisedRandomIncrement)
-
getCurrentValue
abstract double getCurrentValue()
-
getExpected
abstract double getExpected(double stepSize)
-
getLowerConfidenceQuantile
abstract double getLowerConfidenceQuantile(double stepSize, double confidence)
-
getNormalisedRandomIncrement
abstract double getNormalisedRandomIncrement()
-
getStandardDeviation
abstract double getStandardDeviation(double stepSize)
-
getUpperConfidenceQuantile
abstract double getUpperConfidenceQuantile(double stepSize, double confidence)
-
getVariance
abstract double getVariance(double stepSize)
-
setCurrentValue
abstract void setCurrentValue(double currentValue)
-
step
final double step(double stepSize)
-
-