AbramowitzStegun.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>AbramowitzStegun</i> implements the E<sub>2</sub> (erf) Estimator using Abramowitz-Stegun Scheme. 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 abstract class AbramowitzStegun extends org.drip.function.e2erf.ErrorFunction
{
private double _maximumError = java.lang.Double.NaN;
/**
* Construct the Inverse Degree 4 Polynomial Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*
* @return The Inverse Degree 4 Polynomial Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*/
public static final AbramowitzStegun InversePolynomial4()
{
final AbramowitzStegunSeriesGenerator abramowitzStegunSeriesGenerator =
AbramowitzStegunSeriesGenerator.InversePolynomial4();
try
{
return new AbramowitzStegun (
abramowitzStegunSeriesGenerator,
null,
0.0005
)
{
@Override public double evaluate (
final double z)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (z))
{
throw new java.lang.Exception
("AbramowitzStegun::InversePolynomial4::evaluate => Invalid Inputs");
}
if (z < 0)
{
return -1. * evaluate (-1. * z);
}
double erf = 1. - java.lang.Math.pow (
abramowitzStegunSeriesGenerator.cumulative (
0.,
z
),
-4
);
return erf > 1. ? 1. : erf;
}
};
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* Construct the Mixed Degree 3 Polynomial Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*
* @return The Mixed Degree 3 Polynomial Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*/
public static final AbramowitzStegun MixedPolynomial3()
{
final AbramowitzStegunSeriesGenerator abramowitzStegunSeriesGenerator =
AbramowitzStegunSeriesGenerator.MixedPolynomial3();
try
{
return new AbramowitzStegun (
abramowitzStegunSeriesGenerator,
null,
0.000025
)
{
@Override public double evaluate (
final double z)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (z))
{
throw new java.lang.Exception
("AbramowitzStegun::MixedPolynomial3::evaluate => Invalid Inputs");
}
if (z < 0)
{
return -1. * evaluate (-1. * z);
}
double erf = 1. - abramowitzStegunSeriesGenerator.cumulative (
0.,
1. / (1. + 0.47047 * z)
) * java.lang.Math.exp (-1. * z * z);
return erf > 1. ? 1. : erf;
}
};
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* Construct the Inverse Degree 6 Polynomial Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*
* @return The Inverse Degree 6 Polynomial Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*/
public static final AbramowitzStegun InversePolynomial6()
{
final AbramowitzStegunSeriesGenerator abramowitzStegunSeriesGenerator =
AbramowitzStegunSeriesGenerator.InversePolynomial6();
try
{
return new AbramowitzStegun (
abramowitzStegunSeriesGenerator,
null,
0.0000003
)
{
@Override public double evaluate (
final double z)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (z))
{
throw new java.lang.Exception
("AbramowitzStegun::InversePolynomial6::evaluate => Invalid Inputs");
}
if (z < 0)
{
return -1. * evaluate (-1. * z);
}
double erf = 1. - java.lang.Math.pow (
abramowitzStegunSeriesGenerator.cumulative (
0.,
z
),
-16
);
return erf > 1. ? 1. : erf;
}
};
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* Construct the Mixed Degree 5 Polynomial Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*
* @return The Mixed Degree 5 Polynomial Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*/
public static final AbramowitzStegun MixedPolynomial5()
{
final AbramowitzStegunSeriesGenerator abramowitzStegunSeriesGenerator =
AbramowitzStegunSeriesGenerator.MixedPolynomial5();
try
{
return new AbramowitzStegun (
abramowitzStegunSeriesGenerator,
null,
0.00000015
)
{
@Override public double evaluate (
final double z)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (z))
{
throw new java.lang.Exception
("AbramowitzStegun::MixedPolynomial5::evaluate => Invalid Inputs");
}
if (z < 0)
{
return -1. * evaluate (-1. * z);
}
double erf = 1. - abramowitzStegunSeriesGenerator.cumulative (
0.,
1. / (1. + 0.3275911 * z)
) * java.lang.Math.exp (-1. * z * z);
return erf > 1. ? 1. : erf;
}
};
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* Construct the Numerical Recipe Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*
* @return The Numerical Recipe Version of Abramowitz-Stegun E<sub>2</sub> erf Estimator
*/
public static final AbramowitzStegun NumericalRecipe2007()
{
final AbramowitzStegunSeriesGenerator abramowitzStegunSeriesGenerator =
AbramowitzStegunSeriesGenerator.NumericalRecipe2007();
try
{
return new AbramowitzStegun (
abramowitzStegunSeriesGenerator,
null,
0.00000012
)
{
@Override public double evaluate (
final double z)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (z))
{
throw new java.lang.Exception
("AbramowitzStegun::NumericalRecipe2007::evaluate => Invalid Inputs");
}
if (z < 0)
{
return -1. * evaluate (-1. * z);
}
double t = 1. / (1. + 0.5 * z);
double erf = 1. - t * java.lang.Math.exp (
abramowitzStegunSeriesGenerator.cumulative (
0.,
t
) - z * z
);
return erf > 1. ? 1. : erf;
}
};
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* E2AbramowitzStegun Constructor
*
* @param abramowitzStegunSeriesGenerator Abramowitz Stegun Series Generator
* @param dc The Derivative Control
* @param maximumError Maximum Error
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public AbramowitzStegun (
final org.drip.function.e2erf.AbramowitzStegunSeriesGenerator abramowitzStegunSeriesGenerator,
final org.drip.numerical.differentiation.DerivativeControl dc,
final double maximumError)
throws java.lang.Exception
{
super (
abramowitzStegunSeriesGenerator,
dc
);
if (!org.drip.numerical.common.NumberUtil.IsValid (_maximumError = maximumError) || 0. >= _maximumError)
{
throw new java.lang.Exception ("AbramowitzStegun Constructor => Invalid Inputs");
}
}
/**
* Retrieve the Maximum Error
*
* @return The Maximum Error
*/
public double maximumError()
{
return _maximumError;
}
}