Package org.drip.numerical.rdintegration

Class MonteCarloRun

java.lang.Object
org.drip.numerical.rdintegration.MonteCarloRun
Direct Known Subclasses:
MonteCarloRunStratifiedDiagnostics, MonteCarloRunUniformDiagnostics
public class MonteCarloRun
extends java.lang.Object
MonteCarloRun holds the Results of a Rd To R1 Monte-Carlo Integration. The References are:

  • Kroese, D. P., T. Taimre, and Z. I. Botev (2011): Handbook of Monte Carlo Methods John Wiley and Sons Hoboken NJ
  • MacKay, D. (2003): Information Theory, Inference, and Learning Algorithms Cambridge University Press New York NY
  • Newman, M. E. J., and G. T. Barkema (1999): Monte Carlo Methods in Statistical Physics Oxford University Press Oxford UK
  • Press, W. H., S. A. Teukolsky, W. T. Vetterling, B. P. Flannery (2007): Numerical Recipes: The Art of Scientific Computing 3rd Edition Cambridge University Press New York NY
  • Wikipedia (2025): Monte Carlo Integration https://en.wikipedia.org/wiki/Monte_Carlo_integration




Author:
Lakshmi Krishnamurthy

  • Constructor Details

    • MonteCarloRun

      public MonteCarloRun()
      Empty MonteCarloRun Constructor

  • Method Details

    • Merge

      public static final boolean Merge​(MonteCarloRun monteCarloRunMain, MonteCarloRun monteCarloRunTarget)
      Merge the Target Monte Carlo onto the Main
      Parameters:
      monteCarloRunMain - Main Monte Carlo Run
      monteCarloRunTarget - Target Monte Carlo Run
      Returns:
      Merged Monte Carlo Run

    • samplingPointCount

      public int samplingPointCount()
      Retrieve the Count of Sampling Points
      Returns:
      Count of Sampling Points

    • integrandMean

      public double integrandMean()
      Retrieve the Mean Integrand Value
      Returns:
      Mean Integrand Value

    • integrandVolume

      public double integrandVolume()
      Retrieve the Integrand Volume
      Returns:
      Integrand Volume

    • unbiasedIntegrandVariance

      public double unbiasedIntegrandVariance()
      Retrieve the Unbiased Integrand Variance
      Returns:
      Unbiased Integrand Variance

    • setSamplingPointCount

      public boolean setSamplingPointCount​(int samplingPointCount)
      Set the Count of Sampling Points
      Parameters:
      samplingPointCount - Count of Sampling Points
      Returns:
      TRUE - Count of Sampling Points successfully Set

    • setIntegrandMean

      public boolean setIntegrandMean​(double integrandMean)
      Set the Integrand Mean
      Parameters:
      integrandMean - Integrand Mean
      Returns:
      TRUE - The Integrand Mean successfully Set

    • setIntegrandVolume

      public boolean setIntegrandVolume​(double integrandVolume)
      Set the Integrand Volume
      Parameters:
      integrandVolume - Integrand Volume
      Returns:
      TRUE - The Integrand Volume successfully Set

    • setUnbiasedIntegrandVariance

      public boolean setUnbiasedIntegrandVariance​(double unbiasedIntegrandVariance)
      Set the Unbiased Integrand Variance
      Parameters:
      unbiasedIntegrandVariance - Unbiased Integrand Variance
      Returns:
      TRUE - The Unbiased Integrand Variance successfully Set

    • quadratureValue

      public double quadratureValue()
      Retrieve the Quadrature Value
      Returns:
      Quadrature Value

    • quadratureVariance

      public double quadratureVariance()
      Retrieve the Quadrature Variance
      Returns:
      Quadrature Variance

    • quadratureError

      public double quadratureError()
      Retrieve the Quadrature Error
      Returns:
      Quadrature Error

    • quadratureErrorPercent

      public double quadratureErrorPercent()
      Retrieve the Quadrature Error Percent
      Returns:
      Quadrature Error Percent