R1Estimate.java

  1. package org.drip.numerical.estimation;

  3. /*
  4.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  5.  */

  7. /*!
  8.  * Copyright (C) 2020 Lakshmi Krishnamurthy
  9.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  10.  * 
  11.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  12.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  13.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  14.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  15.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  16.  *      and computational support.
  17.  *  
  18.  *      https://lakshmidrip.github.io/DROP/
  19.  *  
  20.  *  DROP is composed of three modules:
  21.  *  
  22.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  23.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  24.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  25.  * 
  26.  *  DROP Product Core implements libraries for the following:
  27.  *  - Fixed Income Analytics
  28.  *  - Loan Analytics
  29.  *  - Transaction Cost Analytics
  30.  * 
  31.  *  DROP Portfolio Core implements libraries for the following:
  32.  *  - Asset Allocation Analytics
  33.  *  - Asset Liability Management Analytics
  34.  *  - Capital Estimation Analytics
  35.  *  - Exposure Analytics
  36.  *  - Margin Analytics
  37.  *  - XVA Analytics
  38.  * 
  39.  *  DROP Computational Core implements libraries for the following:
  40.  *  - Algorithm Support
  41.  *  - Computation Support
  42.  *  - Function Analysis
  43.  *  - Model Validation
  44.  *  - Numerical Analysis
  45.  *  - Numerical Optimizer
  46.  *  - Spline Builder
  47.  *  - Statistical Learning
  48.  * 
  49.  *  Documentation for DROP is Spread Over:
  50.  * 
  51.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  52.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  53.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  54.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  55.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  56.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  57.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  58.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  59.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  60.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  61.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  62.  * 
  63.  *  Licensed under the Apache License, Version 2.0 (the "License");
  64.  *      you may not use this file except in compliance with the License.
  65.  *   
  66.  *  You may obtain a copy of the License at
  67.  *      http://www.apache.org/licenses/LICENSE-2.0
  68.  *  
  69.  *  Unless required by applicable law or agreed to in writing, software
  70.  *      distributed under the License is distributed on an "AS IS" BASIS,
  71.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  72.  *  
  73.  *  See the License for the specific language governing permissions and
  74.  *      limitations under the License.
  75.  */

  77. /**
  78.  * <i>R1Estimate</i> holds the Bounded R<sup>1</sup> Numerical Estimate of a Function. The References are:
  79.  * 
  80.  * <br><br>
  81.  *  <ul>
  82.  *      <li>
  83.  *          Mortici, C. (2011): Improved Asymptotic Formulas for the Gamma Function <i>Computers and
  84.  *              Mathematics with Applications</i> <b>61 (11)</b> 3364-3369
  85.  *      </li>
  86.  *      <li>
  87.  *          National Institute of Standards and Technology (2018): NIST Digital Library of Mathematical
  88.  *              Functions https://dlmf.nist.gov/5.11
  89.  *      </li>
  90.  *      <li>
  91.  *          Nemes, G. (2010): On the Coefficients of the Asymptotic Expansion of n!
  92.  *              https://arxiv.org/abs/1003.2907 <b>arXiv</b>
  93.  *      </li>
  94.  *      <li>
  95.  *          Toth V. T. (2016): Programmable Calculators – The Gamma Function
  96.  *              http://www.rskey.org/CMS/index.php/the-library/11
  97.  *      </li>
  98.  *      <li>
  99.  *          Wikipedia (2019): Stirling's Approximation
  100.  *              https://en.wikipedia.org/wiki/Stirling%27s_approximation
  101.  *      </li>
  102.  *  </ul>
  103.  *
  104.  *  <br><br>
  105.  *  <ul>
  106.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  107.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalAnalysisLibrary.md">Numerical Analysis Library</a></li>
  108.  *      <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>
  109.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/numerical/estimation/README.md">Function Numerical Estimates/Corrections/Bounds</a></li>
  110.  *  </ul>
  111.  *
  112.  * @author Lakshmi Krishnamurthy
  113.  */

  115. public class R1Estimate
  116. {
  117.     private double _baseline = java.lang.Double.NaN;
  118.     private double _lowerBound = java.lang.Double.NaN;
  119.     private double _upperBound = java.lang.Double.NaN;

  121.     private java.util.Map<java.lang.Integer, java.lang.Double> _orderedSeriesMap = new
  122.         java.util.TreeMap<java.lang.Integer, java.lang.Double>();

  124.     /**
  125.      * Construct a Base Line Version without Bounds
  126.      * 
  127.      * @param baseline The Base Line Numerical Estimate
  128.      * 
  129.      * @return The Base Line Version without Bounds
  130.      */

  132.     public static final R1Estimate BaselineOnly (
  133.         final double baseline)
  134.     {
  135.         try
  136.         {
  137.             return new R1Estimate (
  138.                 baseline,
  139.                 java.lang.Double.NaN,
  140.                 java.lang.Double.NaN
  141.             );
  142.         }
  143.         catch (java.lang.Exception e)
  144.         {
  145.             e.printStackTrace();
  146.         }

  148.         return null;
  149.     }

  151.     /**
  152.      * R1Estimate Constructor
  153.      * 
  154.      * @param baseline The Base Line Estimate
  155.      * @param lowerBound The Lower Bound
  156.      * @param upperBound The Upper Bound
  157.      * 
  158.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  159.      */

  161.     public R1Estimate (
  162.         final double baseline,
  163.         final double lowerBound,
  164.         final double upperBound)
  165.         throws java.lang.Exception
  166.     {
  167.         if (!org.drip.numerical.common.NumberUtil.IsValid (_baseline = baseline))
  168.         {
  169.             throw new java.lang.Exception ("R1Estimate Constructor => Invalid Inputs");
  170.         }

  172.         _lowerBound = lowerBound;
  173.         _upperBound = upperBound;
  174.     }

  176.     /**
  177.      * Retrieve the Base Line Numerical Estimate
  178.      * 
  179.      * @return The Base Line Numerical Estimate
  180.      */

  182.     public double baseline()
  183.     {
  184.         return _baseline;
  185.     }

  187.     /**
  188.      * Retrieve the Lower Bound
  189.      * 
  190.      * @return The Lower Bound
  191.      */

  193.     public double lowerBound()
  194.     {
  195.         return _lowerBound;
  196.     }

  198.     /**
  199.      * Retrieve the Upper Bound
  200.      * 
  201.      * @return The Upper Bound
  202.      */

  204.     public double upperBound()
  205.     {
  206.         return _upperBound;
  207.     }

  209.     /**
  210.      * Retrieve the Higher Order Series Map
  211.      * 
  212.      * @return The Higher Order Series Map
  213.      */

  215.     public java.util.Map<java.lang.Integer, java.lang.Double> orderedSeriesMap()
  216.     {
  217.         return _orderedSeriesMap;
  218.     }

  220.     /**
  221.      * Add the Ordered Series Map
  222.      * 
  223.      * @param orderedSeriesMap The Ordered Series Map
  224.      * 
  225.      * @return TRUE - The Ordered Series Map successfully added
  226.      */

  228.     public boolean addOrderedSeriesMap (
  229.         final java.util.Map<java.lang.Integer, java.lang.Double> orderedSeriesMap)
  230.     {
  231.         if (null == orderedSeriesMap)
  232.         {
  233.             return false;
  234.         }

  236.         _orderedSeriesMap = orderedSeriesMap;
  237.         return true;
  238.     }

  240.     /**
  241.      * Retrieve the Series corresponding to the Specified Order
  242.      * 
  243.      * @param order The Series Order
  244.      * 
  245.      * @return The Series corresponding to the Specified Order
  246.      */

  248.     public double orderSeries (
  249.         final int order)
  250.     {
  251.         return _orderedSeriesMap.containsKey (order) ? _orderedSeriesMap.get (order) : 0.;
  252.     }

  254.     /**
  255.      * Compute the Series Cumulative
  256.      * 
  257.      * @return The Series Cumulative
  258.      */

  260.     public double seriesCumulative()
  261.     {
  262.         double seriesCumulative = 0.;

  264.         for (java.util.Map.Entry<java.lang.Integer, java.lang.Double> orderedSeriesEntry :
  265.             _orderedSeriesMap.entrySet())
  266.         {
  267.             seriesCumulative = seriesCumulative + orderedSeriesEntry.getValue();
  268.         }

  270.         return seriesCumulative;
  271.     }
  272. }
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