MacLaurinSeries.java
package org.drip.function.e2erf;
/*
* -*- 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>MacLaurinSeries</i> implements the E<sub>2</sub> MacLaurin Series Term. The References are:
*
* <br><br>
* <ul>
* <li>
* Abramowitz, M., and I. A. Stegun (2007): <i>Handbook of Mathematics Functions</i> <b>Dover Book
* on Mathematics</b>
* </li>
* <li>
* Chang, S. H., P. C. Cosman, L. B. Milstein (2011): Chernoff-Type Bounds for Gaussian Error
* Function <i>IEEE Transactions on Communications</i> <b>59 (11)</b> 2939-2944
* </li>
* <li>
* Cody, W. J. (1991): Algorithm 715: SPECFUN – A Portable FORTRAN Package of Special Function
* Routines and Test Drivers <i>ACM Transactions on Mathematical Software</i> <b>19 (1)</b>
* 22-32
* </li>
* <li>
* Schopf, H. M., and P. H. Supancic (2014): On Burmann’s Theorem and its Application to Problems of
* Linear and Non-linear Heat Transfer and Diffusion
* https://www.mathematica-journal.com/2014/11/on-burmanns-theorem-and-its-application-to-problems-of-linear-and-nonlinear-heat-transfer-and-diffusion/#more-39602/
* </li>
* <li>
* Wikipedia (2019): Error Function https://en.wikipedia.org/wiki/Error_function
* </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/NumericalAnalysisLibrary.md">Numerical Analysis Library</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/function/README.md">R<sup>d</sup> To R<sup>d</sup> Function Analysis</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/function/e2erf/README.md">E<sub>2</sub> erf and erf<sup>-1</sup> Implementations</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class MacLaurinSeries extends org.drip.numerical.estimation.R1ToR1Series
{
/**
* Generate the ERFI E<sub>2</sub> MacLaurin Coefficient corresponding to the specified Series Index
*
* @param seriesIndex Series Index
*
* @return The ERFI E<sub>2</sub> MacLaurin Coefficient corresponding to the specified Series Index
*/
public static final double ERFICoefficient (
final int seriesIndex)
{
if (0 >= seriesIndex)
{
return 1.;
}
double seriesIndexLoader = 0.;
for (int termIndex = 0; termIndex < seriesIndex; ++termIndex)
{
seriesIndexLoader = seriesIndexLoader +
ERFICoefficient (termIndex) * ERFICoefficient (seriesIndex - 1 - termIndex)
/ ((1. + termIndex) * (1. + 2. * termIndex));
}
return seriesIndexLoader;
}
/**
* Construct the E<sub>2</sub> erf MacLaurin Series Generator Version
*
* @param termCount Count of the Number of Terms
*
* @return E<sub>2</sub> erf MacLaurin Series Generator Version
*/
public static final MacLaurinSeries ERF (
final int termCount)
{
java.util.TreeMap<java.lang.Integer, java.lang.Double> termWeightMap = new
java.util.TreeMap<java.lang.Integer, java.lang.Double>();
double signedInverseFactorial = 1.;
for (int termIndex = 0; termIndex <= termCount; ++termIndex)
{
signedInverseFactorial = 0 == termIndex ? 1. : signedInverseFactorial * -1. / termIndex;
termWeightMap.put (
termIndex,
signedInverseFactorial / (2. * termIndex + 1.)
);
}
try
{
return new MacLaurinSeries (
new org.drip.function.e2erf.MacLaurinSeriesTerm(),
termWeightMap
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* Construct the E<sub>2</sub> erfi MacLaurin Series Generator Version
*
* @param termCount Count of the Number of Terms
*
* @return The E<sub>2</sub> erfi MacLaurin Series Generator Version
*/
public static final MacLaurinSeries ERFI (
final int termCount)
{
java.util.TreeMap<java.lang.Integer, java.lang.Double> termWeightMap = new
java.util.TreeMap<java.lang.Integer, java.lang.Double>();
double sqrtPIOver2 = 0.5 * java.lang.Math.sqrt (java.lang.Math.PI);
for (int termIndex = 0; termIndex <= termCount; ++termIndex)
{
int twoKPlusOne = 2 * termIndex + 1;
termWeightMap.put (
termIndex,
(termIndex % 2 == 0 ? 1. : -1.) * ERFICoefficient (termIndex) * java.lang.Math.pow (
sqrtPIOver2,
twoKPlusOne
) / twoKPlusOne
);
}
try
{
return new MacLaurinSeries (
new org.drip.function.e2erf.MacLaurinSeriesTerm(),
termWeightMap
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* MacLaurinSeries Constructor
*
* @param macLaurinSeriesTerm E<sub>2</sub> erf MacLaurin Series Term
* @param termWeightMap Series Term Weight Map
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public MacLaurinSeries (
final org.drip.function.e2erf.MacLaurinSeriesTerm macLaurinSeriesTerm,
final java.util.TreeMap<java.lang.Integer, java.lang.Double> termWeightMap)
throws java.lang.Exception
{
super (
macLaurinSeriesTerm,
false,
termWeightMap
);
}
}