R1UnivariateUniform.java

  1. package org.drip.measure.continuous;

  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>R1UnivariateUniform</i> implements the Univariate R<sup>1</sup> Uniform Distribution. It implements the
  79.  *  Incremental, the Cumulative, and the Inverse Cumulative Distribution Densities.
  80.  *
  81.  *  <br><br>
  82.  *  <ul>
  83.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  84.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalAnalysisLibrary.md">Numerical Analysis Library</a></li>
  85.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/measure/README.md">R<sup>d</sup> Continuous/Discrete Probability Measures</a></li>
  86.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/measure/continuous/README.md">R<sup>1</sup> and R<sup>d</sup> Continuous Random Measure</a></li>
  87.  *  </ul>
  88.  *
  89.  * @author Lakshmi Krishnamurthy
  90.  */

  92. public class R1UnivariateUniform extends org.drip.measure.continuous.R1Univariate
  93. {
  94.     private double _leftSupport = java.lang.Double.NaN;
  95.     private double _rightSupport = java.lang.Double.NaN;

  97.     /**
  98.      * Construct a Standard (0, 1) R<sup>1</sup> Univariate Uniform Distribution
  99.      * 
  100.      * @return Standard (0, 1) R<sup>1</sup> Univariate Uniform Distribution
  101.      */

  103.     public static final R1UnivariateUniform Standard()
  104.     {
  105.         try
  106.         {
  107.             return new R1UnivariateUniform (
  108.                 0.,
  109.                 1.
  110.             );
  111.         }
  112.         catch (java.lang.Exception e)
  113.         {
  114.             e.printStackTrace();
  115.         }

  117.         return null;
  118.     }

  120.     /**
  121.      * R1UnivariateUniform Constructor
  122.      * 
  123.      * @param leftSupport The Left Support
  124.      * @param rightSupport The Right Support
  125.      * 
  126.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  127.      */

  129.     public R1UnivariateUniform (
  130.         final double leftSupport,
  131.         final double rightSupport)
  132.         throws java.lang.Exception
  133.     {
  134.         if (!org.drip.numerical.common.NumberUtil.IsValid (_leftSupport = leftSupport) ||
  135.             !org.drip.numerical.common.NumberUtil.IsValid (_rightSupport = rightSupport) ||
  136.             _leftSupport >= _rightSupport)
  137.         {
  138.             throw new java.lang.Exception ("R1UnivariateUniform Constructor => Invalid Inputs");
  139.         }
  140.     }

  142.     /**
  143.      * Retrieve the Left Support
  144.      * 
  145.      * @return The Left Support
  146.      */

  148.     public double leftSupport()
  149.     {
  150.         return _leftSupport;
  151.     }

  153.     /**
  154.      * Retrieve the Right Support
  155.      * 
  156.      * @return The Right Support
  157.      */

  159.     public double rightSupport()
  160.     {
  161.         return _rightSupport;
  162.     }

  164.     /**
  165.      * Indicate if the specified x Value stays inside the Support
  166.      * 
  167.      * @param x X
  168.      * 
  169.      * @return The Value stays in Support
  170.      */

  172.     public boolean supported (
  173.         final double x)
  174.     {
  175.         return org.drip.numerical.common.NumberUtil.IsValid (x) && x >= _leftSupport || x <= _rightSupport;         
  176.     }

  178.     @Override public double[] support()
  179.     {
  180.         return new double[]
  181.         {
  182.             _leftSupport,
  183.             _rightSupport
  184.         };
  185.     }

  187.     @Override public double cumulative (
  188.         final double x)
  189.         throws java.lang.Exception
  190.     {
  191.         if (!supported (x))
  192.             throw new java.lang.Exception ("R1UnivariateUniform::cumulative => Invalid Inputs");

  194.         return  (x - _leftSupport) / (_rightSupport - _leftSupport);
  195.     }

  197.     @Override public double incremental (
  198.         final double xLeft,
  199.         final double xRight)
  200.         throws java.lang.Exception
  201.     {
  202.         return cumulative (xLeft) - cumulative (xRight);
  203.     }

  205.     @Override public double invCumulative (
  206.         final double y)
  207.         throws java.lang.Exception
  208.     {
  209.         if (!org.drip.numerical.common.NumberUtil.IsValid (y) || 1. < y || 0. > y)
  210.             throw new java.lang.Exception ("R1UnivariateUniform::invCumulative => Cannot calculate");

  212.         return y * (_rightSupport - _leftSupport) + _leftSupport;
  213.     }

  215.     @Override public double density (
  216.         final double x)
  217.         throws java.lang.Exception
  218.     {
  219.         if (!supported (x)) throw new java.lang.Exception ("R1UnivariateUniform::density => Invalid Inputs");

  221.         return 1. / (_rightSupport - _leftSupport);
  222.     }

  224.     @Override public double mean()
  225.     {
  226.         return 0.5 * (_rightSupport + _leftSupport);
  227.     }

  229.     @Override public double variance()
  230.     {
  231.         double support = _rightSupport - _leftSupport;
  232.         return support * support / 12.;
  233.     }

  235.     @Override public double random()
  236.     {
  237.         return java.lang.Math.random() * (_rightSupport - _leftSupport) + _leftSupport;
  238.     }

  240.     @Override public org.drip.numerical.common.Array2D histogram()
  241.     {
  242.         return null;
  243.     }
  244. }
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