IdempotentUnivariateRandom

java.lang.Object

org.drip.function.definition.R1ToR1

org.drip.function.r1tor1operator.OffsetIdempotent

org.drip.sequence.functional.IdempotentUnivariateRandom

Direct Known Subclasses:: BoundedIdempotentUnivariateRandom

public class IdempotentUnivariateRandom
extends OffsetIdempotent

IdempotentUnivariateRandom contains the Implementation of the OffsetIdempotent Objective Function dependent on Univariate Random Variable.

Module = Numerical Core Module
Library = Statistical Learning Library
Project = Sequence
Package = Functional

Author:: Lakshmi Krishnamurthy

Constructor Summary

Constructors

Constructor Description

IdempotentUnivariateRandom(double dblOffset, R1Univariate dist)
IdempotentUnivariateRandom Constructor

Method Summary

Modifier and Type	Method	Description
`SingleSequenceAgnosticMetrics`	`sequenceMetrics()`	Generate the Function Metrics using the Underlying Variate Distribution
`SingleSequenceAgnosticMetrics`	`sequenceMetrics(double[] adblVariateSequence)`	Generate the Function Metrics for the specified Variate Sequence
`SingleSequenceAgnosticMetrics`	`sequenceMetrics(double[] adblVariateSequence, double[] adblVariateWeight)`	Generate the Function Metrics for the specified Variate Sequence and its corresponding Weight
`R1Univariate`	`underlyingDistribution()`	Retrieve the Underlying Distribution

Methods inherited from class org.drip.function.r1tor1operator.OffsetIdempotent

derivative, evaluate, integrate, offset

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

Constructor Details
- IdempotentUnivariateRandom
  
  public IdempotentUnivariateRandom(double dblOffset, R1Univariate dist) throws java.lang.Exception
  
  IdempotentUnivariateRandom Constructor
  
  Parameters:
  
  dblOffset - The Idempotent Offset
  
  dist - The Underlying Distribution
  
  Throws:
  
  java.lang.Exception - Thrown if the Inputs are invalid
Method Details
- 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 Sequence
  
  adblVariateWeight - The specified Variate Weight
  
  Returns:
  
  The Function Sequence Metrics
- sequenceMetrics
  
  public SingleSequenceAgnosticMetrics sequenceMetrics(double[] adblVariateSequence)
  
  Generate the Function Metrics for the specified Variate Sequence
  
  Parameters:
  
  adblVariateSequence - The specified Variate Sequence
  
  Returns:
  
  The Function Sequence Metrics
- sequenceMetrics
  
  public SingleSequenceAgnosticMetrics sequenceMetrics()
  
  Generate the Function Metrics using the Underlying Variate Distribution
  
  Returns:
  
  The Function Sequence Metrics
- underlyingDistribution
  
  public R1Univariate underlyingDistribution()
  
  Retrieve the Underlying Distribution
  
  Returns:
  
  The Underlying Distribution