BoundedIdempotentUnivariateRandom.java

  1. package org.drip.sequence.functional;

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

  5. /*!
  6.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  7.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  8.  * Copyright (C) 2017 Lakshmi Krishnamurthy
  9.  * Copyright (C) 2016 Lakshmi Krishnamurthy
  10.  * Copyright (C) 2015 Lakshmi Krishnamurthy
  11.  *
  12.  *  This file is part of DROP, an open-source library targeting risk, transaction costs, exposure, margin
  13.  *      calculations, and portfolio construction within and across fixed income, credit, commodity, equity,
  14.  *      FX, and structured products.
  15.  *  
  16.  *      https://lakshmidrip.github.io/DROP/
  17.  *  
  18.  *  DROP is composed of three main modules:
  19.  *  
  20.  *  - DROP Analytics Core - https://lakshmidrip.github.io/DROP-Analytics-Core/
  21.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  22.  *  - DROP Numerical Core - https://lakshmidrip.github.io/DROP-Numerical-Core/
  23.  *
  24.  *  DROP Analytics Core implements libraries for the following:
  25.  *  - Fixed Income Analytics
  26.  *  - Asset Backed Analytics
  27.  *  - XVA Analytics
  28.  *  - Exposure and Margin Analytics
  29.  *
  30.  *  DROP Portfolio Core implements libraries for the following:
  31.  *  - Asset Allocation Analytics
  32.  *  - Transaction Cost Analytics
  33.  *
  34.  *  DROP Numerical Core implements libraries for the following:
  35.  *  - Statistical Learning Library
  36.  *  - Numerical Optimizer Library
  37.  *  - Machine Learning Library
  38.  *  - Spline Builder Library
  39.  *
  40.  *  Documentation for DROP is Spread Over:
  41.  *
  42.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  43.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  44.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  45.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  46.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  47.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  48.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  49.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  50.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  51.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  52.  *
  53.  *  Licensed under the Apache License, Version 2.0 (the "License");
  54.  *      you may not use this file except in compliance with the License.
  55.  *  
  56.  *  You may obtain a copy of the License at
  57.  *      http://www.apache.org/licenses/LICENSE-2.0
  58.  *  
  59.  *  Unless required by applicable law or agreed to in writing, software
  60.  *      distributed under the License is distributed on an "AS IS" BASIS,
  61.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  62.  *  
  63.  *  See the License for the specific language governing permissions and
  64.  *      limitations under the License.
  65.  */

  66. /**
  67.  * <i>BoundedIdempotentUnivariateRandom</i> contains the Implementation of the Objective Function dependent
  68.  * on Bounded Idempotent Univariate Random Variable.
  69.  *
  70.  * <br><br>
  71.  *  <ul>
  72.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/NumericalCore.md">Numerical Core Module</a></li>
  73.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/StatisticalLearningLibrary.md">Statistical Learning Library</a></li>
  74.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sequence">Sequence</a></li>
  75.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sequence/functional">Functional</a></li>
  76.  *  </ul>
  77.  * <br><br>
  78.  *
  79.  * @author Lakshmi Krishnamurthy
  80.  */

  81. public class BoundedIdempotentUnivariateRandom extends
  82.     org.drip.sequence.functional.IdempotentUnivariateRandom {
  83.     private double _dblVariateBound = java.lang.Double.NaN;

  84.     /**
  85.      * BoundedIdempotentUnivariateRandom Constructor
  86.      *
  87.      * @param dblOffset The Idempotent Offset
  88.      * @param dist The Underlying Distribution
  89.      * @param dblVariateBound The Variate Bound
  90.      *
  91.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  92.      */

  93.     public BoundedIdempotentUnivariateRandom (
  94.         final double dblOffset,
  95.         final org.drip.measure.continuous.R1Univariate dist,
  96.         final double dblVariateBound)
  97.         throws java.lang.Exception
  98.     {
  99.         super (dblOffset, dist);

  100.         if (!org.drip.numerical.common.NumberUtil.IsValid (_dblVariateBound = dblVariateBound))
  101.             throw new java.lang.Exception ("BoundedIdempotentUnivariateRandom ctr => Invalid Inputs");
  102.     }

  103.     /**
  104.      * Retrieve the Underlying Variate Bound
  105.      *
  106.      * @return The Underlying Variate Bound
  107.      */

  108.     public double variateBound()
  109.     {
  110.         return _dblVariateBound;
  111.     }

  112.     /**
  113.      * Retrieve the Maximal Agnostic Variance Bound Over the Variate Range
  114.      *
  115.      * @return The Maximal Agnostic Bound over the Variate Range
  116.      */

  117.     public double agnosticVarianceBound()
  118.     {
  119.         return _dblVariateBound * _dblVariateBound;
  120.     }
  121. }