Package org.drip.sequence.functional

Class EfronSteinMetrics

java.lang.Object
org.drip.sequence.functional.EfronSteinMetrics
Direct Known Subclasses:
EmpiricalPenaltySupremumMetrics
public class EfronSteinMetrics
extends java.lang.Object
EfronSteinMetrics contains the Variance-based non-exponential Sample Distribution/Bounding Metrics and Agnostic Bounds related to the Functional Transformation of the specified Sequence.



Author:
Lakshmi Krishnamurthy

  • Constructor Details

    • EfronSteinMetrics

      public EfronSteinMetrics​(MultivariateRandom func, SingleSequenceAgnosticMetrics[] aSSAM) throws java.lang.Exception
      EfronSteinMetrics Constructor
      Parameters:
      func - Multivariate Objective Function
      aSSAM - Array of the individual Single Sequence Metrics
      Throws:
      java.lang.Exception - Thrown if the Inputs are Invalid

  • Method Details

    • function

      public RdToR1 function()
      Retrieve the Multivariate Objective Function
      Returns:
      The Multivariate Objective Function Instance

    • sequenceMetrics

      public SingleSequenceAgnosticMetrics[] sequenceMetrics()
      Retrieve the Array of the Single Sequence Agnostic Metrics
      Returns:
      The Array of the Single Sequence Agnostic Metrics

    • variateSequence

      public double[][] variateSequence​(SingleSequenceAgnosticMetrics[] aSSAM)
      Extract the Full Variate Array Sequence
      Parameters:
      aSSAM - Array of the individual Single Sequence Metrics
      Returns:
      The Full Variate Array Sequence

    • variateFunctionVarianceMetrics

      public SingleSequenceAgnosticMetrics[] variateFunctionVarianceMetrics()
      Compute the Function Sequence Agnostic Metrics associated with the Variance of each Variate
      Returns:
      The Array of the Associated Sequence Metrics

    • ghostVariateVarianceMetrics

      public SingleSequenceAgnosticMetrics[] ghostVariateVarianceMetrics​(SingleSequenceAgnosticMetrics[] aSSAMGhost)
      Compute the Function Sequence Agnostic Metrics associated with the Variance of each Variate Using the Supplied Ghost Variate Sequence
      Parameters:
      aSSAMGhost - Array of the Ghost Single Sequence Metrics
      Returns:
      The Array of the Associated Sequence Metrics

    • symmetrizedDifferenceSequenceMetrics

      public SingleSequenceAgnosticMetrics[] symmetrizedDifferenceSequenceMetrics​(SingleSequenceAgnosticMetrics[] aSSAMGhost)
      Compute the Function Sequence Agnostic Metrics associated with each Variate using the specified Ghost Symmetric Variable Copy
      Parameters:
      aSSAMGhost - Array of the Ghost Single Sequence Metrics
      Returns:
      The Array of the Associated Sequence Metrics

    • pivotedDifferenceSequenceMetrics

      public SingleSequenceAgnosticMetrics[] pivotedDifferenceSequenceMetrics​(MultivariateRandom funcPivot)
      Compute the Function Sequence Agnostic Metrics associated with each Variate around the Pivot Point provided by the Pivot Function
      Parameters:
      funcPivot - The Pivot Function
      Returns:
      The Array of the Associated Sequence Metrics

    • martingaleVarianceUpperBound

      public double martingaleVarianceUpperBound() throws java.lang.Exception
      Compute the Multivariate Variance Upper Bound using the Martingale Differences Method
      Returns:
      The Multivariate Variance Upper Bound using the Martingale Differences Method
      Throws:
      java.lang.Exception - Thrown if the Upper Bound cannot be calculated

    • ghostVarianceUpperBound

      public double ghostVarianceUpperBound​(SingleSequenceAgnosticMetrics[] aSSAMGhost) throws java.lang.Exception
      Compute the Variance Upper Bound using the Ghost Variables
      Parameters:
      aSSAMGhost - Array of the Ghost Single Sequence Metrics
      Returns:
      The Variance Upper Bound using the Ghost Variables
      Throws:
      java.lang.Exception - Thrown if the Upper Bound cannot be calculated

    • efronSteinSteeleBound

      public double efronSteinSteeleBound​(SingleSequenceAgnosticMetrics[] aSSAMGhost) throws java.lang.Exception
      Compute the Efron-Stein-Steele Variance Upper Bound using the Ghost Variables
      Parameters:
      aSSAMGhost - Array of the Ghost Single Sequence Metrics
      Returns:
      The Efron-Stein-Steele Variance Upper Bound using the Ghost Variables
      Throws:
      java.lang.Exception - Thrown if the Upper Bound cannot be calculated

    • pivotVarianceUpperBound

      public double pivotVarianceUpperBound​(MultivariateRandom funcPivot) throws java.lang.Exception
      Compute the Function Variance Upper Bound using the supplied Multivariate Pivoting Function
      Parameters:
      funcPivot - The Custom Multivariate Pivoting Function
      Returns:
      The Function Variance Upper Bound using the supplied Multivariate Pivot Function
      Throws:
      java.lang.Exception - Thrown if the Variance Upper Bound cannot be calculated

    • boundedVarianceUpperBound

      public double boundedVarianceUpperBound() throws java.lang.Exception
      Compute the Multivariate Variance Upper Bound using the Bounded Differences Support
      Returns:
      The Multivariate Variance Upper Bound using the Bounded Differences Support
      Throws:
      java.lang.Exception - Thrown if the Upper Bound cannot be calculated

    • separableVarianceUpperBound

      public double separableVarianceUpperBound() throws java.lang.Exception
      Compute the Multivariate Variance Upper Bound using the Separable Variance Bound
      Returns:
      The Multivariate Variance Upper Bound using the Separable Variance Bound
      Throws:
      java.lang.Exception - Thrown if the Upper Bound cannot be calculated