Java Doc for Gamma.java in  » Science » Apache-commons-math-1.1 » org » apache » commons » math » special » Java Source Code / Java DocumentationJava Source Code and Java Documentation

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Java Source Code / Java Documentation » Science » Apache commons math 1.1 » org.apache.commons.math.special   Source Cross Reference   Class Diagram   Java Document (Java Doc)   java.lang.Object    org.apache.commons.math.special.Gamma Gamma public class Gamma implements Serializable(Code) This is a utility class that provides computation methods related to the Gamma family of functions. version:    $Revision: 233121 $ $Date: 2005-08-16 21:41:02 -0700 (Tue, 16 Aug 2005) $ Method Summary public static  double logGamma(double x)      Returns the natural logarithm of the gamma function Γ(x). The implementation of this method is based on: Gamma Function, equation (28). Lanczos Approximation, equations (1) through (5). Paul Godfrey, A note on the computation of the convergent Lanczos complex Gamma approximation Parameters:   x - the value. public static  double regularizedGammaP(double a, double x)      Returns the regularized gamma function P(a, x). Parameters:   a - the a parameter. Parameters:   x - the value. public static  double regularizedGammaP(double a, double x, double epsilon, int maxIterations)      Returns the regularized gamma function P(a, x). The implementation of this method is based on: Regularized Gamma Function, equation (1). Incomplete Gamma Function, equation (4). Confluent Hypergeometric Function of the First Kind, equation (1). Parameters:   a - the a parameter. Parameters:   x - the value. Parameters:   epsilon - When the absolute value of the nth item in theseries is less than epsilon the approximation ceasesto calculate further elements in the series. Parameters:   maxIterations - Maximum number of "iterations" to complete. public static  double regularizedGammaQ(double a, double x)      Returns the regularized gamma function Q(a, x) = 1 - P(a, x). Parameters:   a - the a parameter. Parameters:   x - the value. public static  double regularizedGammaQ(double a, double x, double epsilon, int maxIterations)      Returns the regularized gamma function Q(a, x) = 1 - P(a, x). The implementation of this method is based on: Regularized Gamma Function, equation (1). Regularized incomplete gamma function: Continued fraction representations (formula 06.08.10.0003) Parameters:   a - the a parameter. Parameters:   x - the value. Parameters:   epsilon - When the absolute value of the nth item in theseries is less than epsilon the approximation ceasesto calculate further elements in the series. Parameters:   maxIterations - Maximum number of "iterations" to complete. Method Detail logGamma public static double logGamma(double x)(Code) Returns the natural logarithm of the gamma function Γ(x). The implementation of this method is based on: Gamma Function, equation (28). Lanczos Approximation, equations (1) through (5). Paul Godfrey, A note on the computation of the convergent Lanczos complex Gamma approximation Parameters:   x - the value. log(Γ(x)) regularizedGammaP public static double regularizedGammaP(double a, double x) throws MathException(Code) Returns the regularized gamma function P(a, x). Parameters:   a - the a parameter. Parameters:   x - the value. the regularized gamma function P(a, x) throws:   MathException - if the algorithm fails to converge. regularizedGammaP public static double regularizedGammaP(double a, double x, double epsilon, int maxIterations) throws MathException(Code) Returns the regularized gamma function P(a, x). The implementation of this method is based on: Regularized Gamma Function, equation (1). Incomplete Gamma Function, equation (4). Confluent Hypergeometric Function of the First Kind, equation (1). Parameters:   a - the a parameter. Parameters:   x - the value. Parameters:   epsilon - When the absolute value of the nth item in theseries is less than epsilon the approximation ceasesto calculate further elements in the series. Parameters:   maxIterations - Maximum number of "iterations" to complete. the regularized gamma function P(a, x) throws:   MathException - if the algorithm fails to converge. regularizedGammaQ public static double regularizedGammaQ(double a, double x) throws MathException(Code) Returns the regularized gamma function Q(a, x) = 1 - P(a, x). Parameters:   a - the a parameter. Parameters:   x - the value. the regularized gamma function Q(a, x) throws:   MathException - if the algorithm fails to converge. regularizedGammaQ public static double regularizedGammaQ(double a, double x, double epsilon, int maxIterations) throws MathException(Code) Returns the regularized gamma function Q(a, x) = 1 - P(a, x). The implementation of this method is based on: Regularized Gamma Function, equation (1). Regularized incomplete gamma function: Continued fraction representations (formula 06.08.10.0003) Parameters:   a - the a parameter. Parameters:   x - the value. Parameters:   epsilon - When the absolute value of the nth item in theseries is less than epsilon the approximation ceasesto calculate further elements in the series. Parameters:   maxIterations - Maximum number of "iterations" to complete. the regularized gamma function P(a, x) throws:   MathException - if the algorithm fails to converge. Methods inherited from java.lang.Object native protected Object clone() throws CloneNotSupportedException(Code)(Java Doc) public boolean equals(Object obj)(Code)(Java Doc) protected void finalize() throws Throwable(Code)(Java Doc) final native public Class getClass()(Code)(Java Doc) native public int hashCode()(Code)(Java Doc) final native public void notify()(Code)(Java Doc) final native public void notifyAll()(Code)(Java Doc) public String toString()(Code)(Java Doc) final native public void wait(long timeout) throws InterruptedException(Code)(Java Doc) final public void wait(long timeout, int nanos) throws InterruptedException(Code)(Java Doc) final public void wait() throws InterruptedException(Code)(Java Doc)