LogGammaEstimator.java

  1. package org.drip.specialfunction.beta;

  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>LogGammaEstimator</i> implements the Log Beta Function using the Log Gamma Function. The References
  76.  * are:
  77.  *
  78.  * <br><br>
  79.  *  <ul>
  80.  *      <li>
  81.  *          Abramowitz, M., and I. A. Stegun (2007): <i>Handbook of Mathematics Functions</i> <b>Dover Book
  82.  *              on Mathematics</b>
  83.  *      </li>
  84.  *      <li>
  85.  *          Davis, P. J. (1959): Leonhard Euler's Integral: A Historical Profile of the Gamma Function
  86.  *              <i>American Mathematical Monthly</i> <b>66 (10)</b> 849-869
  87.  *      </li>
  88.  *      <li>
  89.  *          Whitaker, E. T., and G. N. Watson (1996): <i>A Course on Modern Analysis</i> <b>Cambridge
  90.  *              University Press</b> New York
  91.  *      </li>
  92.  *      <li>
  93.  *          Wikipedia (2019): Beta Function https://en.wikipedia.org/wiki/Beta_function
  94.  *      </li>
  95.  *      <li>
  96.  *          Wikipedia (2019): Gamma Function https://en.wikipedia.org/wiki/Gamma_function
  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/FunctionAnalysisLibrary.md">Function Analysis Library</a></li>
  104.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/specialfunction/README.md">Special Function Implementation Analysis</a></li>
  105.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/specialfunction/beta/README.md">Estimation Techniques for Beta Function</a></li>
  106.  *  </ul>
  107.  *
  108.  * @author Lakshmi Krishnamurthy
  109.  */

  110. public class LogGammaEstimator implements org.drip.function.definition.R2ToR1
  111. {
  112.     private org.drip.function.definition.R1ToR1 _r1ToR1LogGamma = null;

  113.     /**
  114.      * Generate the Weierstrass Infinite Product Series Version of Log Beta Estimator
  115.      *
  116.      * @param termCount Number of Terms in the Estimation
  117.      *
  118.      * @return The Weierstrass Infinite Product Series Version of Log Beta Estimator
  119.      */

  120.     public static final LogGammaEstimator Weierstrass (
  121.         final int termCount)
  122.     {
  123.         try
  124.         {
  125.             return new LogGammaEstimator (
  126.                 org.drip.specialfunction.loggamma.InfiniteSumEstimator.Weierstrass (
  127.                     termCount
  128.                 )
  129.             );
  130.         }
  131.         catch (java.lang.Exception e)
  132.         {
  133.             e.printStackTrace();
  134.         }

  135.         return null;
  136.     }

  137.     /**
  138.      * LogGammaBased Constructor
  139.      *
  140.      * @param r1ToR1LogGamma The Log Gamma Function
  141.      *
  142.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  143.      */

  144.     public LogGammaEstimator (
  145.         final org.drip.function.definition.R1ToR1 r1ToR1LogGamma)
  146.         throws java.lang.Exception
  147.     {
  148.         if (null == (_r1ToR1LogGamma = r1ToR1LogGamma))
  149.         {
  150.             throw new java.lang.Exception ("LogGammaEstimator Constructor => Invalid Inputs");
  151.         }
  152.     }

  153.     /**
  154.      * Retrieve the Log Gamma Function
  155.      *
  156.      * @return The Log Gamma Function
  157.      */

  158.     public org.drip.function.definition.R1ToR1 r1ToR1LogGamma()
  159.     {
  160.         return _r1ToR1LogGamma;
  161.     }

  162.     @Override public double evaluate (
  163.         final double x,
  164.         final double y)
  165.         throws java.lang.Exception
  166.     {
  167.         if (!org.drip.numerical.common.NumberUtil.IsValid (x) ||
  168.             !org.drip.numerical.common.NumberUtil.IsValid (y))
  169.         {
  170.             throw new java.lang.Exception ("LogGammaEstimator::evaluate => Invalid Inputs");
  171.         }

  172.         return 0. == x || 0. == y ? 0. : _r1ToR1LogGamma.evaluate (x) + _r1ToR1LogGamma.evaluate (y) -
  173.             _r1ToR1LogGamma.evaluate (x + y);
  174.     }
  175. }