java.lang.Object

org.drip.specialfunction.loggamma.RaabeSeriesEstimator

public class RaabeSeriesEstimator
extends R1ToR1Estimator

RaabeSeriesEstimator implements the Raabe Series Version of Log Gamma Function. This Version is Series Convergent. The References are:

Mortici, C. (2011): Improved Asymptotic Formulas for the Gamma Function Computers and Mathematics with Applications 61 (11) 3364-3369
National Institute of Standards and Technology (2018): NIST Digital Library of Mathematical Functions https://dlmf.nist.gov/5.11
Nemes, G. (2010): On the Coefficients of the Asymptotic Expansion of n! https://arxiv.org/abs/1003.2907 arXiv
Toth V. T. (2016): Programmable Calculators – The Gamma Function http://www.rskey.org/CMS/index.php/the-library/11
Wikipedia (2019): Stirling's Approximation https://en.wikipedia.org/wiki/Stirling%27s_approximation

It provides the following functionality:

RaabeSeriesEstimator Constructor
Compute the Bounded Function Estimates along with the Higher Order Inverted Rising Exponentials
Compute the Raabe's Strip Integral between (a, a + 1) for the Log Gamma Function

Module	Computational Core Module
Library	Function Analysis Library
Project	Special Function Implementation and Analysis
Package	Analytic/Series/Integral Log Gamma Estimators

Method Summary

Modifier and Type	Method	Description
`double`	`evaluate(double x)`	Evaluate for the given variate
`R1Estimate`	`invertedRisingExponentialCorrectionEstimate(double x)`	Compute the Bounded Function Estimates along with the Higher Order Inverted Rising Exponentials
`double`	`stripIntegral(double a)`	Compute the Raabe's Strip Integral between (a, a + 1) for the Log Gamma Function

boundedEstimate, seriesEstimate, seriesEstimateNative

antiDerivative, conditionNumber, derivative, differential, differential, integrate, maxima, maxima, minima, minima, poleResidue

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Class RaabeSeriesEstimator