Package org.drip.sequence.functional
Class FunctionSupremumUnivariateRandom
java.lang.Object
org.drip.function.definition.R1ToR1
org.drip.function.r1tor1.FunctionClassSupremum
org.drip.sequence.functional.FunctionSupremumUnivariateRandom
public class FunctionSupremumUnivariateRandom extends FunctionClassSupremum
FunctionSupremumUnivariateRandom contains the Implementation of the FunctionClassSupremum Objective
Function dependent on Univariate Random Variable.
- Module = Numerical Core Module
- Library = Statistical Learning Library
- Project = Sequence
- Package = Functional
- Author:
- Lakshmi Krishnamurthy
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Constructor Summary
Constructors Constructor Description FunctionSupremumUnivariateRandom(R1ToR1[] aAUClass, R1Univariate dist)
FunctionSupremumUnivariateRandom Constructor -
Method Summary
Modifier and Type Method Description SingleSequenceAgnosticMetrics
sequenceMetrics()
Generate the Function Metrics using the Underlying Variate DistributionSingleSequenceAgnosticMetrics
sequenceMetrics(double[] adblVariateSequence)
Generate the Function Metrics for the specified Variate SequenceSingleSequenceAgnosticMetrics
sequenceMetrics(double[] adblVariateSequence, double[] adblVariateWeight)
Generate the Function Metrics for the specified Variate Sequence and its corresponding WeightR1Univariate
underlyingDistribution()
Retrieve the Underlying DistributionMethods inherited from class org.drip.function.r1tor1.FunctionClassSupremum
derivative, evaluate, functionClass, integrate, supremumFunction
Methods inherited from class org.drip.function.definition.R1ToR1
antiDerivative, conditionNumber, differential, differential, maxima, maxima, minima, minima, poleResidue
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Constructor Details
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FunctionSupremumUnivariateRandom
public FunctionSupremumUnivariateRandom(R1ToR1[] aAUClass, R1Univariate dist) throws java.lang.ExceptionFunctionSupremumUnivariateRandom Constructor- Parameters:
aAUClass
- Array of Functions in the Classdist
- The Underlying Distribution- Throws:
java.lang.Exception
- Thrown if the Inputs are invalid
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Method Details
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sequenceMetrics
public SingleSequenceAgnosticMetrics sequenceMetrics(double[] adblVariateSequence, double[] adblVariateWeight)Generate the Function Metrics for the specified Variate Sequence and its corresponding Weight- Parameters:
adblVariateSequence
- The specified Variate SequenceadblVariateWeight
- The specified Variate Weight- Returns:
- The Function Sequence Metrics
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sequenceMetrics
Generate the Function Metrics for the specified Variate Sequence- Parameters:
adblVariateSequence
- The specified Variate Sequence- Returns:
- The Function Sequence Metrics
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sequenceMetrics
Generate the Function Metrics using the Underlying Variate Distribution- Returns:
- The Function Sequence Metrics
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underlyingDistribution
Retrieve the Underlying Distribution- Returns:
- The Underlying Distribution
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