NestedQuadratureEstimator.java

  1. package org.drip.numerical.integration;

  2. /*
  3.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  4.  */

  5. /*!
  6.  * Copyright (C) 2020 Lakshmi Krishnamurthy
  7.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  8.  *
  9.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  10.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  11.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  12.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  13.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  14.  *      and computational support.
  15.  *  
  16.  *      https://lakshmidrip.github.io/DROP/
  17.  *  
  18.  *  DROP is composed of three modules:
  19.  *  
  20.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  21.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  22.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  23.  *
  24.  *  DROP Product Core implements libraries for the following:
  25.  *  - Fixed Income Analytics
  26.  *  - Loan Analytics
  27.  *  - Transaction Cost Analytics
  28.  *
  29.  *  DROP Portfolio Core implements libraries for the following:
  30.  *  - Asset Allocation Analytics
  31.  *  - Asset Liability Management Analytics
  32.  *  - Capital Estimation Analytics
  33.  *  - Exposure Analytics
  34.  *  - Margin Analytics
  35.  *  - XVA Analytics
  36.  *
  37.  *  DROP Computational Core implements libraries for the following:
  38.  *  - Algorithm Support
  39.  *  - Computation Support
  40.  *  - Function Analysis
  41.  *  - Model Validation
  42.  *  - Numerical Analysis
  43.  *  - Numerical Optimizer
  44.  *  - Spline Builder
  45.  *  - Statistical Learning
  46.  *
  47.  *  Documentation for DROP is Spread Over:
  48.  *
  49.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  50.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  51.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  52.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  53.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  54.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  55.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  56.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  57.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  58.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  59.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  60.  *
  61.  *  Licensed under the Apache License, Version 2.0 (the "License");
  62.  *      you may not use this file except in compliance with the License.
  63.  *  
  64.  *  You may obtain a copy of the License at
  65.  *      http://www.apache.org/licenses/LICENSE-2.0
  66.  *  
  67.  *  Unless required by applicable law or agreed to in writing, software
  68.  *      distributed under the License is distributed on an "AS IS" BASIS,
  69.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  70.  *  
  71.  *  See the License for the specific language governing permissions and
  72.  *      limitations under the License.
  73.  */

  74. /**
  75.  * <i>NestedQuadratureEstimator</i> extends the R<sup>1</sup> Quadrature Estimator by providing the
  76.  * Estimation Error. The References are:
  77.  *
  78.  * <br><br>
  79.  *  <ul>
  80.  *      <li>
  81.  *          Briol, F. X., C. J. Oates, M. Girolami, and M. A. Osborne (2015): <i>Frank-Wolfe Bayesian
  82.  *              Quadrature: Probabilistic Integration with Theoretical Guarantees</i> <b>arXiv</b>
  83.  *      </li>
  84.  *      <li>
  85.  *          Forsythe, G. E., M. A. Malcolm, and C. B. Moler (1977): <i>Computer Methods for Mathematical
  86.  *              Computation</i> <b>Prentice Hall</b> Englewood Cliffs NJ
  87.  *      </li>
  88.  *      <li>
  89.  *          Leader, J. J. (2004): <i>Numerical Analysis and Scientific Computation</i> <b>Addison Wesley</b>
  90.  *      </li>
  91.  *      <li>
  92.  *          Stoer, J., and R. Bulirsch (1980): <i>Introduction to Numerical Analysis</i>
  93.  *              <b>Springer-Verlag</b> New York
  94.  *      </li>
  95.  *      <li>
  96.  *          Wikipedia (2019): Numerical Integration https://en.wikipedia.org/wiki/Numerical_integration
  97.  *      </li>
  98.  *  </ul>
  99.  *
  100.  *  <br><br>
  101.  *  <ul>
  102.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  103.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalAnalysisLibrary.md">Numerical Analysis Library</a></li>
  104.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/numerical/README.md">Numerical Quadrature, Differentiation, Eigenization, Linear Algebra, and Utilities</a></li>
  105.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/numerical/integration/README.md">R<sup>1</sup> R<sup>d</sup> Numerical Integration Schemes</a></li>
  106.  *  </ul>
  107.  *
  108.  * @author Lakshmi Krishnamurthy
  109.  */

  110. public class NestedQuadratureEstimator extends org.drip.numerical.integration.QuadratureEstimator
  111. {
  112.     private org.drip.numerical.integration.QuadratureEstimator _embeddedQuadratureEstimator = null;

  113.     /**
  114.      * NestedQuadratureEstimator Constructor
  115.      *
  116.      * @param abscissaTransformer The Abscissa Transformer
  117.      * @param nodeWeightArray Array of the Nodes and Weights
  118.      * @param embeddedQuadratureEstimator The Embedded Quadrature Estimator
  119.      *
  120.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  121.      */

  122.     public NestedQuadratureEstimator (
  123.         final org.drip.numerical.integration.AbscissaTransform abscissaTransformer,
  124.         final org.drip.numerical.common.Array2D nodeWeightArray,
  125.         final org.drip.numerical.integration.QuadratureEstimator embeddedQuadratureEstimator)
  126.         throws java.lang.Exception
  127.     {
  128.         super (
  129.             abscissaTransformer,
  130.             nodeWeightArray
  131.         );

  132.         if (null == (_embeddedQuadratureEstimator = embeddedQuadratureEstimator))
  133.         {
  134.             throw new java.lang.Exception ("NestedQuadratureEstimator Constructor => Invalid Inputs");
  135.         }
  136.     }

  137.     /**
  138.      * Retrieve the Embedded Quadrature Estimator
  139.      *
  140.      * @return The Embedded Quadrature Estimator
  141.      */

  142.     public org.drip.numerical.integration.QuadratureEstimator embeddedQuadratureEstimator()
  143.     {
  144.         return _embeddedQuadratureEstimator;
  145.     }

  146.     /**
  147.      * Estimate the Quadrature and its Error
  148.      *
  149.      * @param r1ToR1Integrand The R<sup>1</sup> To R<sup>1</sup> Integrand
  150.      *
  151.      * @return The Quadrature and its Error
  152.      */

  153.     public org.drip.numerical.integration.QuadratureEstimate estimate (
  154.         final org.drip.function.definition.R1ToR1 r1ToR1Integrand)
  155.     {
  156.         try
  157.         {
  158.             double baseline = integrate (r1ToR1Integrand);

  159.             return new org.drip.numerical.integration.QuadratureEstimate (
  160.                 baseline,
  161.                 java.lang.Math.abs (baseline - _embeddedQuadratureEstimator.integrate (r1ToR1Integrand))
  162.             );
  163.         }
  164.         catch (java.lang.Exception e)
  165.         {
  166.             e.printStackTrace();
  167.         }

  168.         return null;
  169.     }
  170. }