LogBigPi.java

package org.drip.specialfunction.derived;

/*
 * -*- 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>LogBigPi</i> implements the Log Gaussian Big Pi from the Log Gamma Function. The References are:
 * 
 * <br><br>
 *  <ul>
 *      <li>
 *          Blagouchine, I. V. (2014): Re-discovery of Malmsten's Integrals, their Evaluation by Contour
 *              Integration Methods, and some Related Results <i>Ramanujan Journal</i> <b>35 (1)</b> 21-110
 *      </li>
 *      <li>
 *          Borwein, J. M., and R. M. Corless (2017): Gamma Function and the Factorial in the Monthly
 *              https://arxiv.org/abs/1703.05349 <b>arXiv</b>
 *      </li>
 *      <li>
 *          Davis, P. J. (1959): Leonhard Euler's Integral: A Historical Profile of the Gamma Function
 *              <i>American Mathematical Monthly</i> <b>66 (10)</b> 849-869
 *      </li>
 *      <li>
 *          Whitaker, E. T., and G. N. Watson (1996): <i>A Course on Modern Analysis</i> <b>Cambridge
 *              University Press</b> New York
 *      </li>
 *      <li>
 *          Wikipedia (2019): Gamma Function https://en.wikipedia.org/wiki/Gamma_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/FunctionAnalysisLibrary.md">Function Analysis Library</a></li>
 *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/specialfunction/README.md">Special Function Implementation Analysis</a></li>
 *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/specialfunction/derived/README.md">Special Functions Derived using Others</a></li>
 *  </ul>
 *
 * @author Lakshmi Krishnamurthy
 */

public class LogBigPi extends org.drip.function.definition.R1ToR1
{
    private org.drip.function.definition.R1ToR1 _logGammaEstimator = null;

    /**
     * Generate the Weierstrass Infinite Sum Series Version of Log Big Pi Estimator
     * 
     * @param termCount Number of Terms in the Estimation
     * 
     * @return The Weierstrass Infinite Sum Series Version of Log Big Pi Estimator
     */

    public static final LogBigPi Weierstrass (
        final int termCount)
    {
        try
        {
            return new LogBigPi (org.drip.specialfunction.loggamma.InfiniteSumEstimator.Weierstrass (termCount));
        }
        catch (java.lang.Exception e)
        {
            e.printStackTrace();
        }

        return null;
    }

    /**
     * Compute the Volume of the N-Ellipsoid
     * 
     * @param termCount Number of Terms in the Estimation
     * @param radiusArray The Array of the Ellipsoid Radii
     * 
     * @return The Volume of the N-Ellipsoid
     * 
     * @throws java.lang.Exception Thrown if the Inputs are Invalid
     */

    public static final double NEllipsoidVolume (
        final int termCount,
        final double[] radiusArray)
        throws java.lang.Exception
    {
        if (null == radiusArray)
        {
            throw new java.lang.Exception ("LogBigPi::NEllipsoidVolume => Invalid Inputs");
        }

        int radiusCount = radiusArray.length;

        if (0 == radiusCount || org.drip.numerical.common.NumberUtil.IsValid (radiusArray))
        {
            throw new java.lang.Exception ("LogBigPi::NEllipsoidVolume => Invalid Inputs");
        }

        double halfN = 0.5 * radiusCount;

        double logNEllipsoidVolume = halfN * java.lang.Math.log (java.lang.Math.PI) -
            Weierstrass (termCount).evaluate (halfN);

        for (int radiusIndex = 0; radiusIndex < radiusCount; ++radiusIndex)
        {
            logNEllipsoidVolume = logNEllipsoidVolume + radiusArray[radiusIndex];
        }

        return java.lang.Math.exp (logNEllipsoidVolume);
    }

    /**
     * LogBigPi Constructor
     * 
     * @param logGammaEstimator The Log Gamma Estimator
     * 
     * @throws java.lang.Exception Thrown if the Inputs are Invalid
     */

    public LogBigPi (
        final org.drip.function.definition.R1ToR1 logGammaEstimator)
        throws java.lang.Exception
    {
        super (null);

        if (null == (_logGammaEstimator = logGammaEstimator))
        {
            throw new java.lang.Exception ("LogBigPi Constructor => Invalid Inputs");
        }
    }

    /**
     * Retrieve the Log Gamma Estimator
     * 
     * @return The Log Gamma Estimator
     */

    public org.drip.function.definition.R1ToR1 logGammaEstimator()
    {
        return _logGammaEstimator;
    }

    @Override public double evaluate (
        final double z)
        throws java.lang.Exception
    {
        if (!org.drip.numerical.common.NumberUtil.IsValid (z))
        {
            throw new java.lang.Exception ("LogBigPi::evaluate => Invalid Inputs");
        }

        return _logGammaEstimator.evaluate (z + 1.);
    }
}