KnottedRegressionSplineEstimator.java
package org.drip.sample.stretch;
import org.drip.numerical.common.FormatUtil;
import org.drip.spline.basis.*;
import org.drip.spline.params.*;
import org.drip.spline.stretch.*;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* 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 DRIP, a free-software/open-source library for buy/side financial/trading model
* libraries targeting analysts and developers
* https://lakshmidrip.github.io/DRIP/
*
* DRIP is composed of four main libraries:
*
* - DRIP Fixed Income - https://lakshmidrip.github.io/DRIP-Fixed-Income/
* - DRIP Asset Allocation - https://lakshmidrip.github.io/DRIP-Asset-Allocation/
* - DRIP Numerical Optimizer - https://lakshmidrip.github.io/DRIP-Numerical-Optimizer/
* - DRIP Statistical Learning - https://lakshmidrip.github.io/DRIP-Statistical-Learning/
*
* - DRIP Fixed Income: Library for Instrument/Trading Conventions, Treasury Futures/Options,
* Funding/Forward/Overnight Curves, Multi-Curve Construction/Valuation, Collateral Valuation and XVA
* Metric Generation, Calibration and Hedge Attributions, Statistical Curve Construction, Bond RV
* Metrics, Stochastic Evolution and Option Pricing, Interest Rate Dynamics and Option Pricing, LMM
* Extensions/Calibrations/Greeks, Algorithmic Differentiation, and Asset Backed Models and Analytics.
*
* - DRIP Asset Allocation: Library for model libraries for MPT framework, Black Litterman Strategy
* Incorporator, Holdings Constraint, and Transaction Costs.
*
* - DRIP Numerical Optimizer: Library for Numerical Optimization and Spline Functionality.
*
* - DRIP Statistical Learning: Library for Statistical Evaluation and Machine Learning.
*
* 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.
*/
/**
* KnottedRegressionSplineEstimator shows the sample construction and usage of Knot-based Regression Splines.
* It demonstrates construction of the segment's predictor ordinate/response value combination, and eventual
* calibration.
*
* @author Lakshmi Krishnamurthy
*/
public class KnottedRegressionSplineEstimator {
/*
* Build Polynomial Segment Control Parameters
*
* WARNING: Insufficient Error Checking, so use caution
*/
private static final SegmentCustomBuilderControl PolynomialSegmentControlParams (
final int iNumBasis,
final SegmentInelasticDesignControl sdic)
throws Exception
{
return new SegmentCustomBuilderControl (
MultiSegmentSequenceBuilder.BASIS_SPLINE_POLYNOMIAL,
new PolynomialFunctionSetParams (iNumBasis),
sdic,
null,
null
);
}
/*
* Basis Spline Stretch Test Sample. Performs the following:
* - Construct the Array of Segment Builder Parameters - one per segment.
* - Construct a Stretch instance using the predictor ordinate array and the Segment Best Fit Response Values.
* - Estimate, compute the segment-by-segment monotonicity and the Stretch Jacobian
* - Compute the Segment Curvature Penalty Estimate.
*
* WARNING: Insufficient Error Checking, so use caution
*/
private static final void BasisSplineStretchTest (
final double[] adblX,
final SegmentCustomBuilderControl scbc,
final StretchBestFitResponse sbfr)
throws Exception
{
double dblX = 1.;
double dblXMax = 10.;
/*
* Array of Segment Builder Parameters - one per segment
*/
SegmentCustomBuilderControl[] aSCBC = new SegmentCustomBuilderControl[adblX.length - 1];
for (int i = 0; i < adblX.length - 1; ++i)
aSCBC[i] = scbc;
/*
* Construct a Stretch instance using the predictor ordinate array and the Segment Best Fit Response Values
*/
MultiSegmentSequence mss = MultiSegmentSequenceBuilder.CreateRegressionSplineEstimator (
"SPLINE_STRETCH",
adblX, // predictors
aSCBC, // Basis Segment Builder parameters
sbfr,
BoundarySettings.NaturalStandard(), // Boundary Condition - Natural
MultiSegmentSequence.CALIBRATE // Calibrate the Stretch predictors to the responses
);
/*
* Estimate, compute the segment-by-segment monotonicity and the Stretch Jacobian
*/
while (dblX <= dblXMax) {
System.out.println ("Y[" + dblX + "] " + FormatUtil.FormatDouble (mss.responseValue (dblX), 1, 2, 1.) + " | " +
mss.monotoneType (dblX));
System.out.println ("\t\tJacobian Y[" + dblX + "]=" + mss.jackDResponseDCalibrationInput (dblX, 1).displayString());
dblX += 1.;
}
/*
* Compute the Segment Curvature Penalty Estimate
*/
System.out.println ("\tSPLINE_STRETCH DPE: " + mss.curvatureDPE());
}
/*
* Bring together to compose the Regression Spline Estimator Test. It is made up of the following steps:
* - Set the Predictor Ordinate Knot Points.
* - Construct a set of Predictor Ordinates, their Responses, and corresponding Weights to serve as
* weighted closeness of fit.
* - Construct the segment inelastic parameter that is C2 (iK = 2 sets it to C2), with 2nd order
* roughness penalty derivative, and without constraint.
* - Basis Spline Stretch Test Using the Segment Best Fit Response.
*
* WARNING: Insufficient Error Checking, so use caution
*/
private static final void RegressionSplineEstimatorTest()
throws Exception
{
/*
* Set the Knot Points
*/
double[] adblX = new double[] { 1.00, 5.00, 10.00};
/*
* Construct a set of Predictor Ordinates, their Responses, and corresponding Weights to serve as
* weighted closeness of fit.
*/
StretchBestFitResponse sbfr = StretchBestFitResponse.Create (
new double[] { 2.28, 2.52, 2.73, 3.00, 5.50, 8.44, 8.76, 9.08, 9.80, 9.92},
new double[] {14.27, 12.36, 10.61, 9.25, -0.50, 7.92, 10.07, 12.23, 15.51, 16.36},
new double[] { 1.09, 0.82, 1.34, 1.10, 0.50, 0.79, 0.65, 0.49, 0.24, 0.21}
);
/*
* Construct the segment inelastic parameter that is C2 (iK = 2 sets it to C2), with 2nd order
* roughness penalty derivative, and without constraint
*/
int iK = 2;
int iRoughnessPenaltyDerivativeOrder = 2;
SegmentInelasticDesignControl sdic = SegmentInelasticDesignControl.Create (
iK,
iRoughnessPenaltyDerivativeOrder
);
int iPolyNumBasis = 4;
/*
* Basis Spline Stretch Test Using the Segment Best Fit Response
*/
BasisSplineStretchTest (
adblX,
PolynomialSegmentControlParams (
iPolyNumBasis,
sdic
),
sbfr
);
}
public static final void main (
final String[] astrArgs)
throws Exception
{
RegressionSplineEstimatorTest();
}
}