R1Estimate.java
package org.drip.numerical.estimation;
/*
* -*- 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>R1Estimate</i> holds the Bounded R<sup>1</sup> Numerical Estimate of a Function. The References are:
*
* <br><br>
* <ul>
* <li>
* Mortici, C. (2011): Improved Asymptotic Formulas for the Gamma Function <i>Computers and
* Mathematics with Applications</i> <b>61 (11)</b> 3364-3369
* </li>
* <li>
* National Institute of Standards and Technology (2018): NIST Digital Library of Mathematical
* Functions https://dlmf.nist.gov/5.11
* </li>
* <li>
* Nemes, G. (2010): On the Coefficients of the Asymptotic Expansion of n!
* https://arxiv.org/abs/1003.2907 <b>arXiv</b>
* </li>
* <li>
* Toth V. T. (2016): Programmable Calculators – The Gamma Function
* http://www.rskey.org/CMS/index.php/the-library/11
* </li>
* <li>
* Wikipedia (2019): Stirling's Approximation
* https://en.wikipedia.org/wiki/Stirling%27s_approximation
* </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/numerical/README.md">Numerical Quadrature, Differentiation, Eigenization, Linear Algebra, and Utilities</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/numerical/estimation/README.md">Function Numerical Estimates/Corrections/Bounds</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class R1Estimate
{
private double _baseline = java.lang.Double.NaN;
private double _lowerBound = java.lang.Double.NaN;
private double _upperBound = java.lang.Double.NaN;
private java.util.Map<java.lang.Integer, java.lang.Double> _orderedSeriesMap = new
java.util.TreeMap<java.lang.Integer, java.lang.Double>();
/**
* Construct a Base Line Version without Bounds
*
* @param baseline The Base Line Numerical Estimate
*
* @return The Base Line Version without Bounds
*/
public static final R1Estimate BaselineOnly (
final double baseline)
{
try
{
return new R1Estimate (
baseline,
java.lang.Double.NaN,
java.lang.Double.NaN
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
/**
* R1Estimate Constructor
*
* @param baseline The Base Line Estimate
* @param lowerBound The Lower Bound
* @param upperBound The Upper Bound
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public R1Estimate (
final double baseline,
final double lowerBound,
final double upperBound)
throws java.lang.Exception
{
if (!org.drip.numerical.common.NumberUtil.IsValid (_baseline = baseline))
{
throw new java.lang.Exception ("R1Estimate Constructor => Invalid Inputs");
}
_lowerBound = lowerBound;
_upperBound = upperBound;
}
/**
* Retrieve the Base Line Numerical Estimate
*
* @return The Base Line Numerical Estimate
*/
public double baseline()
{
return _baseline;
}
/**
* Retrieve the Lower Bound
*
* @return The Lower Bound
*/
public double lowerBound()
{
return _lowerBound;
}
/**
* Retrieve the Upper Bound
*
* @return The Upper Bound
*/
public double upperBound()
{
return _upperBound;
}
/**
* Retrieve the Higher Order Series Map
*
* @return The Higher Order Series Map
*/
public java.util.Map<java.lang.Integer, java.lang.Double> orderedSeriesMap()
{
return _orderedSeriesMap;
}
/**
* Add the Ordered Series Map
*
* @param orderedSeriesMap The Ordered Series Map
*
* @return TRUE - The Ordered Series Map successfully added
*/
public boolean addOrderedSeriesMap (
final java.util.Map<java.lang.Integer, java.lang.Double> orderedSeriesMap)
{
if (null == orderedSeriesMap)
{
return false;
}
_orderedSeriesMap = orderedSeriesMap;
return true;
}
/**
* Retrieve the Series corresponding to the Specified Order
*
* @param order The Series Order
*
* @return The Series corresponding to the Specified Order
*/
public double orderSeries (
final int order)
{
return _orderedSeriesMap.containsKey (order) ? _orderedSeriesMap.get (order) : 0.;
}
/**
* Compute the Series Cumulative
*
* @return The Series Cumulative
*/
public double seriesCumulative()
{
double seriesCumulative = 0.;
for (java.util.Map.Entry<java.lang.Integer, java.lang.Double> orderedSeriesEntry :
_orderedSeriesMap.entrySet())
{
seriesCumulative = seriesCumulative + orderedSeriesEntry.getValue();
}
return seriesCumulative;
}
}