ErrorFunctionInverse.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>ErrorFunctionInverse</i> implements the E<sub>2</sub> erf Inverse erf<sup>-1</sup>. 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 ErrorFunctionInverse extends org.drip.numerical.estimation.R1ToR1Estimator
{
private org.drip.numerical.estimation.R1ToR1Series _r1ToR1SeriesGenerator = null;
/**
* Construct Winitzki (2008) Version of the Analytical E<sub>2</sub> erf Inverse
*
* @param a a
*
* @return Winitzki (2008) Version of the Analytical E<sub>2</sub> erf Inverse
*/
public static final org.drip.function.e2erf.ErrorFunctionInverse Winitzki2008 (
final double a)
{
try
{
return !org.drip.numerical.common.NumberUtil.IsValid (a) ? null :
new org.drip.function.e2erf.ErrorFunctionInverse (
null,
null
)
{
@Override public double evaluate (
final double z)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (z) || z <= -1. || z >= 1.)
{
throw new java.lang.Exception
("ErrorFunctionInverse::Winitzki2008::evaluate => Invalid Inputs");
}
if (0. == z)
{
return 0.;
}
if (0. > z)
{
return -1. * evaluate (-1. * z);
}
double twoOverPIA = 2. / (java.lang.Math.PI * a);
double lnOneMinusZ2 = java.lang.Math.log (1. - z * z);
double halfLnOneMinusZ2 = 0.5 * lnOneMinusZ2;
double twoOverPIAPlusHalfLnOneMinusZ2 = twoOverPIA + halfLnOneMinusZ2;
double erfi = java.lang.Math.sqrt (
java.lang.Math.sqrt (
twoOverPIAPlusHalfLnOneMinusZ2 * twoOverPIAPlusHalfLnOneMinusZ2 -
(lnOneMinusZ2 / a)
) - twoOverPIAPlusHalfLnOneMinusZ2
);
return erfi < 0. ? -1. * erfi : erfi;
}
};
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* Construct Winitzki (2008a) Version of the Analytical E<sub>2</sub> erf Inverse
*
* @return Winitzki (2008a) Version of the Analytical E<sub>2</sub> erf Inverse
*/
public static final org.drip.function.e2erf.ErrorFunctionInverse Winitzki2008a()
{
return Winitzki2008 (
8. * (java.lang.Math.PI - 3.) / (3. * java.lang.Math.PI * (4. - java.lang.Math.PI))
);
}
/**
* Construct Winitzki (2008b) Version of the Analytical E<sub>2</sub> erf Inverse
*
* @return Winitzki (2008b) Version of the Analytical E<sub>2</sub> erf Inverse
*/
public static final org.drip.function.e2erf.ErrorFunctionInverse Winitzki2008b()
{
return Winitzki2008 (0.147);
}
/**
* Construct the Euler-MacLaurin Instance of the E<sub>2</sub> erf Inverse
*
* @param termCount The Count of Approximation Terms
*
* @return The Euler-MacLaurin Instance of the E<sub>2</sub> erf Inverse
*/
public static final ErrorFunctionInverse MacLaurin (
final int termCount)
{
final org.drip.function.e2erf.MacLaurinSeries e2InverseMacLaurinSeriesGenerator =
org.drip.function.e2erf.MacLaurinSeries.ERFI (termCount);
if (null == e2InverseMacLaurinSeriesGenerator)
{
return null;
}
return new ErrorFunctionInverse (
e2InverseMacLaurinSeriesGenerator,
null
)
{
@Override public double evaluate (
final double z)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (z) || -1. >= z || 1. <= z)
{
throw new java.lang.Exception
("ErrorFunctionInverse::MacLaurin::evaluate => Invalid Inputs");
}
double erfi = e2InverseMacLaurinSeriesGenerator.cumulative (
0.,
z
);
return erfi > 1. ? 1. : erfi;
}
};
}
protected ErrorFunctionInverse (
final org.drip.numerical.estimation.R1ToR1Series r1ToR1SeriesGenerator,
final org.drip.numerical.differentiation.DerivativeControl dc)
{
super (dc);
_r1ToR1SeriesGenerator = r1ToR1SeriesGenerator;
}
@Override public org.drip.numerical.estimation.R1Estimate seriesEstimateNative (
final double x)
{
return null == _r1ToR1SeriesGenerator ? seriesEstimate (
x,
null,
null
) : seriesEstimate (
x,
_r1ToR1SeriesGenerator.termWeightMap(),
_r1ToR1SeriesGenerator
);
}
/**
* Compute the Probit Value for the given p
*
* @param p P
*
* @return The Probit Value
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public double probit (
final double p)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (p))
{
throw new java.lang.Exception ("ErrorFunctionInverse::probit => Invalid Inputs");
}
return java.lang.Math.sqrt (2.) * evaluate (2. * p - 1.);
}
/**
* Compute the Inverse CDF Value for the given p
*
* @param p P
*
* @return The Inverse CDF Value
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public double inverseCDF (
final double p)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (p))
{
throw new java.lang.Exception ("ErrorFunctionInverse::inverseCDF => Invalid Inputs");
}
return java.lang.Math.sqrt (2.) * evaluate (2. * p - 1.);
}
}