Package org.drip.validation.distance

Class ImportanceWeight

java.lang.Object
org.drip.validation.distance.ImportanceWeight
public class ImportanceWeight
extends java.lang.Object
ImportanceWeight weighs the Importance of each Empirical Hypothesis Outcome.

  • Anfuso, F., D. Karyampas, and A. Nawroth (2017): A Sound Basel III Compliant Framework for Back-testing Credit Exposure Models https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2264620 eSSRN
  • Diebold, F. X., T. A. Gunther, and A. S. Tay (1998): Evaluating Density Forecasts with Applications to Financial Risk Management, International Economic Review 39 (4) 863-883
  • Kenyon, C., and R. Stamm (2012): Discounting, LIBOR, CVA, and Funding: Interest Rate and Credit Pricing Palgrave Macmillan
  • Wikipedia (2018): Probability Integral Transform https://en.wikipedia.org/wiki/Probability_integral_transform
  • Wikipedia (2019): p-value https://en.wikipedia.org/wiki/P-value




Author:
Lakshmi Krishnamurthy

  • Constructor Summary

    Constructors
    Constructor Description
    ImportanceWeight​(R1Univariate r1Univariate, double positiveExpectation)
    ImportanceWeight Constructor

  • Method Summary

    Modifier and Type Method Description
    static ImportanceWeight Normal​(R1UnivariateNormal r1UnivariateNormal)
    Construct the Importance Weight Version based on Normal Distribution
    double positiveExpectation()
    Retrieve the Positive Expectation
    double quantileLoading​(double q)
    Retrieve the Importance Weight Loading given the Quantile
    R1Univariate r1Univariate()
    Retrieve the Underlying R1 Distribution

    Methods inherited from class java.lang.Object

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

  • Constructor Details

    • ImportanceWeight

      public ImportanceWeight​(R1Univariate r1Univariate, double positiveExpectation) throws java.lang.Exception
      ImportanceWeight Constructor
      Parameters:
      r1Univariate - The Underlying R1 Distribution
      positiveExpectation - The Positive Expectation
      Throws:
      java.lang.Exception - Thrown if the Inputs are Invalid

  • Method Details

    • Normal

      public static final ImportanceWeight Normal​(R1UnivariateNormal r1UnivariateNormal)
      Construct the Importance Weight Version based on Normal Distribution
      Parameters:
      r1UnivariateNormal - R1 Normal Distribution
      Returns:
      The Importance Weight

    • positiveExpectation

      public double positiveExpectation()
      Retrieve the Positive Expectation
      Returns:
      The Positive Expectation

    • r1Univariate

      public R1Univariate r1Univariate()
      Retrieve the Underlying R1 Distribution
      Returns:
      The Underlying R1 Distribution

    • quantileLoading

      public double quantileLoading​(double q) throws java.lang.Exception
      Retrieve the Importance Weight Loading given the Quantile
      Parameters:
      q - The Quantile
      Returns:
      The Importance Weight Loading
      Throws:
      java.lang.Exception - Thrown if the Inputs are Invalid