R1R1.java

  1. package org.drip.measure.continuous;

  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.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  9.  * Copyright (C) 2017 Lakshmi Krishnamurthy
  10.  * Copyright (C) 2016 Lakshmi Krishnamurthy
  11.  * Copyright (C) 2015 Lakshmi Krishnamurthy
  12.  *
  13.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  14.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  15.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  16.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  17.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  18.  *      and computational support.
  19.  *  
  20.  *      https://lakshmidrip.github.io/DROP/
  21.  *  
  22.  *  DROP is composed of three modules:
  23.  *  
  24.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  25.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  26.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  27.  *
  28.  *  DROP Product Core implements libraries for the following:
  29.  *  - Fixed Income Analytics
  30.  *  - Loan Analytics
  31.  *  - Transaction Cost Analytics
  32.  *
  33.  *  DROP Portfolio Core implements libraries for the following:
  34.  *  - Asset Allocation Analytics
  35.  *  - Asset Liability Management Analytics
  36.  *  - Capital Estimation Analytics
  37.  *  - Exposure Analytics
  38.  *  - Margin Analytics
  39.  *  - XVA Analytics
  40.  *
  41.  *  DROP Computational Core implements libraries for the following:
  42.  *  - Algorithm Support
  43.  *  - Computation Support
  44.  *  - Function Analysis
  45.  *  - Model Validation
  46.  *  - Numerical Analysis
  47.  *  - Numerical Optimizer
  48.  *  - Spline Builder
  49.  *  - Statistical Learning
  50.  *
  51.  *  Documentation for DROP is Spread Over:
  52.  *
  53.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  54.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  55.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  56.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  57.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  58.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  59.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  60.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  61.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  62.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  63.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  64.  *
  65.  *  Licensed under the Apache License, Version 2.0 (the "License");
  66.  *      you may not use this file except in compliance with the License.
  67.  *  
  68.  *  You may obtain a copy of the License at
  69.  *      http://www.apache.org/licenses/LICENSE-2.0
  70.  *  
  71.  *  Unless required by applicable law or agreed to in writing, software
  72.  *      distributed under the License is distributed on an "AS IS" BASIS,
  73.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  74.  *  
  75.  *  See the License for the specific language governing permissions and
  76.  *      limitations under the License.
  77.  */

  78. /**
  79.  * <i>R1R1</i> implements the Base Abstract Class behind Bivariate R<sup>1</sup> Distributions. It exports
  80.  * Methods for Incremental, Cumulative, and Inverse Cumulative Distribution Densities.
  81.  *
  82.  *  <br><br>
  83.  *  <ul>
  84.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
  85.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalAnalysisLibrary.md">Numerical Analysis Library</a></li>
  86.  *      <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>
  87.  *      <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>
  88.  *  </ul>
  89.  *
  90.  * @author Lakshmi Krishnamurthy
  91.  */

  92. public abstract class R1R1 {

  93.     /**
  94.      * Compute the Cumulative under the Distribution to the given Variate Pair
  95.      *
  96.      * @param dblX R^1 The X Variate to which the Cumulative is to be computed
  97.      * @param dblY R^1 The Y Variate to which the Cumulative is to be computed
  98.      *
  99.      * @return The Cumulative under the Distribution to the given Variate Pair
  100.      *
  101.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  102.      */

  103.     public abstract double cumulative (
  104.         final double dblX,
  105.         final double dblY)
  106.         throws java.lang.Exception;

  107.     /**
  108.      * Compute the Incremental under the Distribution between the Variate Pair
  109.      *
  110.      * @param dblXLeft R^1 Left X Variate from which the Cumulative is to be computed
  111.      * @param dblYLeft R^1 Left Y Variate from which the Cumulative is to be computed
  112.      * @param dblXRight R^1 Right X Variate to which the Cumulative is to be computed
  113.      * @param dblYRight R^1 Right Y Variate to which the Cumulative is to be computed
  114.      *
  115.      * @return The Incremental under the Distribution between the Variate Pair
  116.      *
  117.      * @throws java.lang.Exception Thrown if the inputs are invalid
  118.      */

  119.     public abstract double incremental (
  120.         final double dblXLeft,
  121.         final double dblYLeft,
  122.         final double dblXRight,
  123.         final double dblYRight)
  124.         throws java.lang.Exception;

  125.     /**
  126.      * Compute the Density under the Distribution at the given Variate Pair
  127.      *
  128.      * @param dblX R^1 The Variate to which the Cumulative is to be computed
  129.      * @param dblY R^1 The Variate to which the Cumulative is to be computed
  130.      *
  131.      * @return The Density under the Distribution at the given Variate Pair
  132.      *
  133.      * @throws java.lang.Exception Thrown if the Input is Invalid
  134.      */

  135.     public abstract double density (
  136.         final double dblX,
  137.         final double dblY)
  138.         throws java.lang.Exception;
  139. }