LagrangePolynomialStretchRegressor.java
package org.drip.regression.spline;
/*
* -*- 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
* Copyright (C) 2012 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>LagrangePolynomialStretchRegressor</i> implements the local control basis spline regressor for the
* given basis spline. As part of the regression run, it executes the following:
*
* <br><br>
* <ul>
* <li>
* Calibrate and compute the left and the right Jacobian.
* </li>
* <li>
* Insert the Local Control Hermite, Cardinal, and Catmull-Rom knots.
* </li>
* <li>
* Compute an intermediate value Jacobian.
* </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/ComputationSupportLibrary.md">Computation Support</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/regression/README.md">Regression Engine Core and the Unit Regressors</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/regression/spline/README.md">Custom Basis Spline Regression Engine</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class LagrangePolynomialStretchRegressor extends org.drip.regression.core.UnitRegressionExecutor {
private boolean _bLocallyMonotone = false;
private double _dblValue = java.lang.Double.NaN;
private org.drip.spline.segment.Monotonocity _sm = null;
private org.drip.numerical.differentiation.WengertJacobian _wj = null;
private org.drip.spline.stretch.SingleSegmentSequence _sss = null;
public LagrangePolynomialStretchRegressor (
final java.lang.String strName,
final java.lang.String strScenarioName)
throws java.lang.Exception
{
super (strName, strScenarioName);
_sss = new org.drip.spline.stretch.SingleSegmentLagrangePolynomial (new double[] {1., 2., 3., 4.});
}
@Override public boolean preRegression()
{
try {
return _sss.setup (1., new double[] {1., 2., 3., 4.}, null,
org.drip.spline.stretch.BoundarySettings.NaturalStandard(),
org.drip.spline.stretch.MultiSegmentSequence.CALIBRATE);
} catch (java.lang.Exception e) {
e.printStackTrace();
}
return false;
}
@Override public boolean execRegression()
{
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (_dblValue = _sss.responseValue (2.16)))
return false;
_bLocallyMonotone = _sss.isLocallyMonotone();
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
if (null == (_wj = _sss.jackDResponseDCalibrationInput (2.16, 1))) return false;
return null != (_sm = _sss.monotoneType (2.16));
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
if (!rnvd.set ("LPSR_Value", "" + _dblValue)) return false;
if (!rnvd.set ("LPSR_WJ", _wj.displayString())) return false;
if (!rnvd.set ("LPSR_SM", _sm.toString())) return false;
return rnvd.set ("LPSR_LocallyMonotone", "" + _bLocallyMonotone);
}
}