KnottedRegressionSplineEstimator.java

  1. package org.drip.sample.stretch;

  3. import org.drip.numerical.common.FormatUtil;
  4. import org.drip.spline.basis.*;
  5. import org.drip.spline.params.*;
  6. import org.drip.spline.stretch.*;

  8. /*
  9.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  10.  */

  12. /*!
  13.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  14.  * Copyright (C) 2017 Lakshmi Krishnamurthy
  15.  * Copyright (C) 2016 Lakshmi Krishnamurthy
  16.  * Copyright (C) 2015 Lakshmi Krishnamurthy
  17.  * Copyright (C) 2014 Lakshmi Krishnamurthy
  18.  * Copyright (C) 2013 Lakshmi Krishnamurthy
  19.  * 
  20.  *  This file is part of DRIP, a free-software/open-source library for buy/side financial/trading model
  21.  *      libraries targeting analysts and developers
  22.  *      https://lakshmidrip.github.io/DRIP/
  23.  *  
  24.  *  DRIP is composed of four main libraries:
  25.  *  
  26.  *  - DRIP Fixed Income - https://lakshmidrip.github.io/DRIP-Fixed-Income/
  27.  *  - DRIP Asset Allocation - https://lakshmidrip.github.io/DRIP-Asset-Allocation/
  28.  *  - DRIP Numerical Optimizer - https://lakshmidrip.github.io/DRIP-Numerical-Optimizer/
  29.  *  - DRIP Statistical Learning - https://lakshmidrip.github.io/DRIP-Statistical-Learning/
  30.  * 
  31.  *  - DRIP Fixed Income: Library for Instrument/Trading Conventions, Treasury Futures/Options,
  32.  *      Funding/Forward/Overnight Curves, Multi-Curve Construction/Valuation, Collateral Valuation and XVA
  33.  *      Metric Generation, Calibration and Hedge Attributions, Statistical Curve Construction, Bond RV
  34.  *      Metrics, Stochastic Evolution and Option Pricing, Interest Rate Dynamics and Option Pricing, LMM
  35.  *      Extensions/Calibrations/Greeks, Algorithmic Differentiation, and Asset Backed Models and Analytics.
  36.  * 
  37.  *  - DRIP Asset Allocation: Library for model libraries for MPT framework, Black Litterman Strategy
  38.  *      Incorporator, Holdings Constraint, and Transaction Costs.
  39.  * 
  40.  *  - DRIP Numerical Optimizer: Library for Numerical Optimization and Spline Functionality.
  41.  * 
  42.  *  - DRIP Statistical Learning: Library for Statistical Evaluation and Machine Learning.
  43.  * 
  44.  *  Licensed under the Apache License, Version 2.0 (the "License");
  45.  *      you may not use this file except in compliance with the License.
  46.  *   
  47.  *  You may obtain a copy of the License at
  48.  *      http://www.apache.org/licenses/LICENSE-2.0
  49.  *  
  50.  *  Unless required by applicable law or agreed to in writing, software
  51.  *      distributed under the License is distributed on an "AS IS" BASIS,
  52.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  53.  *  
  54.  *  See the License for the specific language governing permissions and
  55.  *      limitations under the License.
  56.  */

  58. /**
  59.  * KnottedRegressionSplineEstimator shows the sample construction and usage of Knot-based Regression Splines.
  60.  *  It demonstrates construction of the segment's predictor ordinate/response value combination, and eventual
  61.  *  calibration.
  62.  *
  63.  * @author Lakshmi Krishnamurthy
  64.  */

  66. public class KnottedRegressionSplineEstimator {

  68.     /*
  69.      * Build Polynomial Segment Control Parameters
  70.      * 
  71.      *  WARNING: Insufficient Error Checking, so use caution
  72.      */

  74.     private static final SegmentCustomBuilderControl PolynomialSegmentControlParams (
  75.         final int iNumBasis,
  76.         final SegmentInelasticDesignControl sdic)
  77.         throws Exception
  78.     {
  79.         return new SegmentCustomBuilderControl (
  80.             MultiSegmentSequenceBuilder.BASIS_SPLINE_POLYNOMIAL,
  81.             new PolynomialFunctionSetParams (iNumBasis),
  82.             sdic,
  83.             null,
  84.             null
  85.         );
  86.     }

  88.     /*
  89.      * Basis Spline Stretch Test Sample. Performs the following:
  90.      *  - Construct the Array of Segment Builder Parameters - one per segment.
  91.      *  - Construct a Stretch instance using the predictor ordinate array and the Segment Best Fit Response Values.
  92.      *  - Estimate, compute the segment-by-segment monotonicity and the Stretch Jacobian
  93.      *  - Compute the Segment Curvature Penalty Estimate.
  94.      * 
  95.      *  WARNING: Insufficient Error Checking, so use caution
  96.      */

  98.     private static final void BasisSplineStretchTest (
  99.         final double[] adblX,
  100.         final SegmentCustomBuilderControl scbc,
  101.         final StretchBestFitResponse sbfr)
  102.         throws Exception
  103.     {
  104.         double dblX = 1.;
  105.         double dblXMax = 10.;

  107.         /*
  108.          * Array of Segment Builder Parameters - one per segment
  109.          */

  111.         SegmentCustomBuilderControl[] aSCBC = new SegmentCustomBuilderControl[adblX.length - 1]; 

  113.         for (int i = 0; i < adblX.length - 1; ++i)
  114.             aSCBC[i] = scbc;

  116.         /*
  117.          * Construct a Stretch instance using the predictor ordinate array and the Segment Best Fit Response Values
  118.          */

  120.         MultiSegmentSequence mss = MultiSegmentSequenceBuilder.CreateRegressionSplineEstimator (
  121.             "SPLINE_STRETCH",
  122.             adblX, // predictors
  123.             aSCBC, // Basis Segment Builder parameters
  124.             sbfr,
  125.             BoundarySettings.NaturalStandard(), // Boundary Condition - Natural
  126.             MultiSegmentSequence.CALIBRATE // Calibrate the Stretch predictors to the responses
  127.         );

  129.         /*
  130.          * Estimate, compute the segment-by-segment monotonicity and the Stretch Jacobian
  131.          */

  133.         while (dblX <= dblXMax) {
  134.             System.out.println ("Y[" + dblX + "] " + FormatUtil.FormatDouble (mss.responseValue (dblX), 1, 2, 1.) + " | " +
  135.                 mss.monotoneType (dblX));

  137.             System.out.println ("\t\tJacobian Y[" + dblX + "]=" + mss.jackDResponseDCalibrationInput (dblX, 1).displayString());

  139.             dblX += 1.;
  140.         }

  142.         /*
  143.          * Compute the Segment Curvature Penalty Estimate
  144.          */

  146.         System.out.println ("\tSPLINE_STRETCH DPE: " + mss.curvatureDPE());
  147.     }

  149.     /*
  150.      * Bring together to compose the Regression Spline Estimator Test. It is made up of the following steps:
  151.      *  - Set the Predictor Ordinate Knot Points.
  152.      *  - Construct a set of Predictor Ordinates, their Responses, and corresponding Weights to serve as
  153.      *      weighted closeness of fit.
  154.      *  - Construct the segment inelastic parameter that is C2 (iK = 2 sets it to C2), with 2nd order
  155.      *      roughness penalty derivative, and without constraint.
  156.      *  - Basis Spline Stretch Test Using the Segment Best Fit Response.
  157.      * 
  158.      *  WARNING: Insufficient Error Checking, so use caution
  159.      */

  161.     private static final void RegressionSplineEstimatorTest()
  162.         throws Exception
  163.     {
  164.         /*
  165.          * Set the Knot Points
  166.          */

  168.         double[] adblX = new double[] { 1.00,  5.00, 10.00};

  170.         /*
  171.          * Construct a set of Predictor Ordinates, their Responses, and corresponding Weights to serve as
  172.          *  weighted closeness of fit.
  173.          */

  175.         StretchBestFitResponse sbfr = StretchBestFitResponse.Create (
  176.             new double[] { 2.28,  2.52,  2.73, 3.00,  5.50, 8.44,  8.76,  9.08,  9.80,  9.92},
  177.             new double[] {14.27, 12.36, 10.61, 9.25, -0.50, 7.92, 10.07, 12.23, 15.51, 16.36},
  178.             new double[] { 1.09,  0.82,  1.34, 1.10,  0.50, 0.79,  0.65,  0.49,  0.24,  0.21}
  179.         );

  181.         /*
  182.          * Construct the segment inelastic parameter that is C2 (iK = 2 sets it to C2), with 2nd order
  183.          *  roughness penalty derivative, and without constraint
  184.          */

  186.         int iK = 2;
  187.         int iRoughnessPenaltyDerivativeOrder = 2;

  189.         SegmentInelasticDesignControl sdic = SegmentInelasticDesignControl.Create (
  190.             iK,
  191.             iRoughnessPenaltyDerivativeOrder
  192.         );

  194.         int iPolyNumBasis = 4;

  196.         /*
  197.          * Basis Spline Stretch Test Using the Segment Best Fit Response
  198.          */

  200.         BasisSplineStretchTest (
  201.             adblX,
  202.             PolynomialSegmentControlParams (
  203.                 iPolyNumBasis,
  204.                 sdic
  205.             ),
  206.             sbfr
  207.         );
  208.     }

  210.     public static final void main (
  211.         final String[] astrArgs)
  212.         throws Exception
  213.     {
  214.         RegressionSplineEstimatorTest();
  215.     }
  216. }
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