PredictorResponseRelationSetup.java
package org.drip.state.estimator;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2020 Lakshmi Krishnamurthy
* Copyright (C) 2019 Lakshmi Krishnamurthy
* Copyright (C) 2018 Lakshmi Krishnamurthy
* Copyright (C) 2017 Lakshmi Krishnamurthy
* Copyright (C) 2016 Lakshmi Krishnamurthy
* Copyright (C) 2015 Lakshmi Krishnamurthy
* Copyright (C) 2014 Lakshmi Krishnamurthy
* Copyright (C) 2013 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>PredictorResponseRelationSetup</i> holds the Linearized Constraints (and, optionally, their quote
* sensitivities) necessary needed for the Linear Calibration. Linearized Constraints are expressed as
*
* Sum_i[Predictor Weight_i * Function (Response_i)] = Constraint Value
*
* where Function can either be univariate function, or weighted spline basis set. To this end, it implements
* the following functionality:
*
* <br><br>
* <ul>
* <li>
* Update/Retrieve Predictor/Response Weights and their Quote Sensitivities
* </li>
* <li>
* Update/Retrieve Predictor/Response Constraint Values and their Quote Sensitivities
* </li>
* <li>
* Display the contents of PredictorResponseRelationSetup
* </li>
* </ul>
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ProductCore.md">Product Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/FixedIncomeAnalyticsLibrary.md">Fixed Income Analytics</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/state/README.md">Latent State Inference and Creation Utilities</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/state/estimator/README.md">Multi-Pass Customized Stretch Curve</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class PredictorResponseRelationSetup {
private double _dblValue = 0.;
private java.util.TreeMap<java.lang.Double, java.lang.Double> _mapPredictorResponseWeight = new
java.util.TreeMap<java.lang.Double, java.lang.Double>();
/**
* Empty PredictorResponseRelationSetup constructor
*/
public PredictorResponseRelationSetup()
{
}
/**
* Update the Constraint Value
*
* @param dblValue The Constraint Value Update Increment
*
* @return TRUE - This Update Succeeded
*/
public boolean updateValue (
final double dblValue)
{
if (!org.drip.numerical.common.NumberUtil.IsValid (dblValue)) return false;
_dblValue += dblValue;
return true;
}
/**
* Add a Predictor/Response Weight entry to the Linearized Constraint
*
* @param dblPredictor The Predictor Node
* @param dblResponseWeight The Response Weight at the Node
*
* @return TRUE - Successfully added
*/
public boolean addPredictorResponseWeight (
final double dblPredictor,
final double dblResponseWeight)
{
if (!org.drip.numerical.common.NumberUtil.IsValid (dblPredictor) ||
!org.drip.numerical.common.NumberUtil.IsValid (dblResponseWeight))
return false;
double dblResponseWeightPrior = _mapPredictorResponseWeight.containsKey (dblPredictor) ?
_mapPredictorResponseWeight.get (dblPredictor) : 0.;
_mapPredictorResponseWeight.put (dblPredictor, dblResponseWeight + dblResponseWeightPrior);
return true;
}
/**
* Retrieve the Constraint Value
*
* @return The Constraint Value
*/
public double getValue()
{
return _dblValue;
}
/**
* Retrieve the Predictor To-From Response Weight Map
*
* @return The Predictor To-From Response Weight Map
*/
public java.util.TreeMap<java.lang.Double, java.lang.Double> getPredictorResponseWeight()
{
return _mapPredictorResponseWeight;
}
/**
* Absorb the "Other" PRRS onto the current one
*
* @param prrsOther The "Other" PRRS
*
* @return TRUE - At least one Entry was absorbed
*/
public boolean absorb (
final PredictorResponseRelationSetup prrsOther)
{
if (null == prrsOther || !updateValue (prrsOther.getValue())) return false;
java.util.TreeMap<java.lang.Double, java.lang.Double> mapPRWOther =
prrsOther.getPredictorResponseWeight();
if (null == mapPRWOther || 0 == mapPRWOther.size()) return true;
for (java.util.Map.Entry<java.lang.Double, java.lang.Double> me : mapPRWOther.entrySet()) {
if (null != me && !addPredictorResponseWeight (me.getKey(), me.getValue())) return false;
}
return true;
}
}