HypothesisOutcomeSuite.java

package org.drip.validation.distance;

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

/*!
 * Copyright (C) 2020 Lakshmi Krishnamurthy
 * Copyright (C) 2019 Lakshmi Krishnamurthy
 * 
 *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
 *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
 *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
 *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
 *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
 *      and computational support.
 *  
 *      https://lakshmidrip.github.io/DROP/
 *  
 *  DROP is composed of three modules:
 *  
 *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
 *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
 *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
 * 
 *  DROP Product Core implements libraries for the following:
 *  - Fixed Income Analytics
 *  - Loan Analytics
 *  - Transaction Cost Analytics
 * 
 *  DROP Portfolio Core implements libraries for the following:
 *  - Asset Allocation Analytics
 *  - Asset Liability Management Analytics
 *  - Capital Estimation Analytics
 *  - Exposure Analytics
 *  - Margin Analytics
 *  - XVA Analytics
 * 
 *  DROP Computational Core implements libraries for the following:
 *  - Algorithm Support
 *  - Computation Support
 *  - Function Analysis
 *  - Model Validation
 *  - Numerical Analysis
 *  - Numerical Optimizer
 *  - Spline Builder
 *  - Statistical Learning
 * 
 *  Documentation for DROP is Spread Over:
 * 
 *  - Main                     => https://lakshmidrip.github.io/DROP/
 *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
 *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
 *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
 *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
 *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
 *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
 *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
 *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
 *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
 *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
 * 
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *      you may not use this file except in compliance with the License.
 *   
 *  You may obtain a copy of the License at
 *      http://www.apache.org/licenses/LICENSE-2.0
 *  
 *  Unless required by applicable law or agreed to in writing, software
 *      distributed under the License is distributed on an "AS IS" BASIS,
 *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  
 *  See the License for the specific language governing permissions and
 *      limitations under the License.
 */

/**
 * <i>HypothesisOutcomeSuite</i> holds the Map of Hypotheses Outcomes to be subjected to Discriminatory Power
 * Analysis.
 *
 *  <br><br>
 *  <ul>
 *      <li>
 *          Anfuso, F., D. Karyampas, and A. Nawroth (2017): A Sound Basel III Compliant Framework for
 *              Back-testing Credit Exposure Models
 *              https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2264620 <b>eSSRN</b>
 *      </li>
 *      <li>
 *          Diebold, F. X., T. A. Gunther, and A. S. Tay (1998): Evaluating Density Forecasts with
 *              Applications to Financial Risk Management, International Economic Review 39 (4) 863-883
 *      </li>
 *      <li>
 *          Kenyon, C., and R. Stamm (2012): <i>Discounting, LIBOR, CVA, and Funding: Interest Rate and
 *              Credit Pricing</i> <b>Palgrave Macmillan</b>
 *      </li>
 *      <li>
 *          Wikipedia (2018): Probability Integral Transform
 *              https://en.wikipedia.org/wiki/Probability_integral_transform
 *      </li>
 *      <li>
 *          Wikipedia (2019): p-value https://en.wikipedia.org/wiki/P-value
 *      </li>
 *  </ul>
 *
 *  <br><br>
 *  <ul>
 *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
 *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ModelValidationAnalyticsLibrary.md">Model Validation Analytics Library</a></li>
 *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/validation/README.md">Risk Factor and Hypothesis Validation, Evidence Processing, and Model Testing</a></li>
 *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/validation/distance/README.md">Hypothesis Target Distance Test Builders</a></li>
 *  </ul>
 * <br><br>
 *
 * @author Lakshmi Krishnamurthy
 */

public class HypothesisOutcomeSuite
{
    private java.util.Map<java.lang.String, org.drip.validation.distance.GapTestOutcome> _outcomeMap = new
        org.drip.analytics.support.CaseInsensitiveHashMap<org.drip.validation.distance.GapTestOutcome>();

    private java.util.TreeMap<java.lang.Double, java.lang.String> _distanceHypothesisMap = new
        java.util.TreeMap<java.lang.Double, java.lang.String>();

    /**
     * Empty HypothesisOutcomeSuite Constructor
     */

    public HypothesisOutcomeSuite()
    {
    }

    /**
     * Retrieve the Outcome Map
     * 
     * @return The Outcome Map
     */

    public java.util.Map<java.lang.String, org.drip.validation.distance.GapTestOutcome> outcomeMap()
    {
        return _outcomeMap;
    }

    /**
     * Retrieve the Distance-Hypothesis Map
     * 
     * @return The Distance-Hypothesis Map
     */

    public java.util.TreeMap<java.lang.Double, java.lang.String> distanceHypothesisMap()
    {
        return _distanceHypothesisMap;
    }

    /**
     * Add a Hypothesis - Outcome Instance
     * 
     * @param hypothesisID Hypothesis ID
     * @param gapTestOutcome Gap Test Outcome
     * 
     * @return TRUE - The Hypothesis - Outcome successfully added
     */

    public boolean add (
        final java.lang.String hypothesisID,
        final org.drip.validation.distance.GapTestOutcome gapTestOutcome)
    {
        if (null == hypothesisID || hypothesisID.isEmpty() ||
            null == gapTestOutcome)
        {
            return false;
        }

        _outcomeMap.put (
            hypothesisID,
            gapTestOutcome
        );

        _distanceHypothesisMap.put (
            gapTestOutcome.distance(),
            hypothesisID
        );

        return true;
    }

    /**
     * Retrieve the Leading/Best Fit Hypothesis and its Test Outcome
     * 
     * @return The Leading/Best Fit Hypothesis and its Test Outcome
     */

    public org.drip.validation.distance.HypothesisOutcome leadingHypothesis()
    {
        if (0 == _distanceHypothesisMap.size())
        {
            return null;
        }

        java.lang.String leadingHypothesisID = _distanceHypothesisMap.firstEntry().getValue();

        try
        {
            return new org.drip.validation.distance.HypothesisOutcome (
                leadingHypothesisID,
                _outcomeMap.get (leadingHypothesisID)
            );
        }
        catch (java.lang.Exception e)
        {
            e.printStackTrace();
        }

        return null;
    }
}