org.apache.commons.math.special
Class Gamma

java.lang.Object
  extended by org.apache.commons.math.special.Gamma

public class Gamma
extends Object

This is a utility class that provides computation methods related to the Gamma family of functions.

Version:
$Revision: 1042510 $ $Date: 2010-12-06 02:54:18 +0100 (lun. 06 déc. 2010) $

Field Summary
static double GAMMA
          Euler-Mascheroni constant
 
Method Summary
static double digamma(double x)
          Computes the digamma function of x.
static double logGamma(double x)
          Returns the natural logarithm of the gamma function Γ(x).
static double regularizedGammaP(double a, double x)
          Returns the regularized gamma function P(a, x).
static double regularizedGammaP(double a, double x, double epsilon, int maxIterations)
          Returns the regularized gamma function P(a, x).
static double regularizedGammaQ(double a, double x)
          Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
static double regularizedGammaQ(double a, double x, double epsilon, int maxIterations)
          Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
static double trigamma(double x)
          Computes the trigamma function of x.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

GAMMA

public static final double GAMMA
Euler-Mascheroni constant

Since:
2.0
See Also:
Constant Field Values
Method Detail

logGamma

public static double logGamma(double x)
Returns the natural logarithm of the gamma function Γ(x). The implementation of this method is based on:

Parameters:
x - the value.
Returns:
log(Γ(x))

regularizedGammaP

public static double regularizedGammaP(double a,
                                       double x)
                                throws MathException
Returns the regularized gamma function P(a, x).

Parameters:
a - the a parameter.
x - the value.
Returns:
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
Returns the regularized gamma function P(a, x). The implementation of this method is based on:

Parameters:
a - the a parameter.
x - the value.
epsilon - When the absolute value of the nth item in the series is less than epsilon the approximation ceases to calculate further elements in the series.
maxIterations - Maximum number of "iterations" to complete.
Returns:
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
Returns the regularized gamma function Q(a, x) = 1 - P(a, x).

Parameters:
a - the a parameter.
x - the value.
Returns:
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
Returns the regularized gamma function Q(a, x) = 1 - P(a, x). The implementation of this method is based on:

Parameters:
a - the a parameter.
x - the value.
epsilon - When the absolute value of the nth item in the series is less than epsilon the approximation ceases to calculate further elements in the series.
maxIterations - Maximum number of "iterations" to complete.
Returns:
the regularized gamma function P(a, x)
Throws:
MathException - if the algorithm fails to converge.

digamma

public static double digamma(double x)

Computes the digamma function of x.

This is an independently written implementation of the algorithm described in Jose Bernardo, Algorithm AS 103: Psi (Digamma) Function, Applied Statistics, 1976.

Some of the constants have been changed to increase accuracy at the moderate expense of run-time. The result should be accurate to within 10^-8 absolute tolerance for x >= 10^-5 and within 10^-8 relative tolerance for x > 0.

Performance for large negative values of x will be quite expensive (proportional to |x|). Accuracy for negative values of x should be about 10^-8 absolute for results less than 10^5 and 10^-8 relative for results larger than that.

Parameters:
x - the argument
Returns:
digamma(x) to within 10-8 relative or absolute error whichever is smaller
Since:
2.0
See Also:
Digamma at wikipedia , Bernardo's original article

trigamma

public static double trigamma(double x)

Computes the trigamma function of x. This function is derived by taking the derivative of the implementation of digamma.

Parameters:
x - the argument
Returns:
trigamma(x) to within 10-8 relative or absolute error whichever is smaller
Since:
2.0
See Also:
Trigamma at wikipedia , digamma(double)


Copyright © 2003-2011 Apache Software Foundation. All Rights Reserved.