org.apache.commons.math3.special

## Class Gamma

• public class Gamma
extends Object

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

Implementation of invGamma1pm1(double) and logGamma1p(double) is based on the algorithms described in

and implemented in the NSWC Library of Mathematical Functions, available here. This library is "approved for public release", and the Copyright guidance indicates that unless otherwise stated in the code, all FORTRAN functions in this library are license free. Since no such notice appears in the code these functions can safely be ported to Commons-Math.

Version:
$Id: Gamma.java 1422313 2012-12-15 18:53:41Z psteitz$
• ### Field Summary

Fields
Modifier and Type Field and Description
static double GAMMA
static double LANCZOS_G
The value of the g constant in the Lanczos approximation, see lanczos(double).
• ### Method Summary

Methods
Modifier and Type Method and Description
static double digamma(double x)
Computes the digamma function of x.
static double gamma(double x)
Returns the value of Γ(x).
static double invGamma1pm1(double x)
Returns the value of 1 / Γ(1 + x) - 1 for -0.5 ≤ x ≤ 1.5.
static double lanczos(double x)
Returns the Lanczos approximation used to compute the gamma function.
static double logGamma(double x)
Returns the value of log Γ(x) for x > 0.
static double logGamma1p(double x)
Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5.
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
• ### Method Detail

• #### regularizedGammaP

public static double regularizedGammaP(double a,
double x)
Returns the regularized gamma function P(a, x).
Parameters:
a - Parameter.
x - Value.
Returns:
the regularized gamma function P(a, x).
Throws:
MaxCountExceededException - if the algorithm fails to converge.
• #### regularizedGammaP

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:
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:
MaxCountExceededException - if the algorithm fails to converge.
• #### regularizedGammaQ

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.
x - the value.
Returns:
the regularized gamma function Q(a, x)
Throws:
MaxCountExceededException - if the algorithm fails to converge.
• #### regularizedGammaQ

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:
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:
MaxCountExceededException - 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 - Argument.
Returns:
digamma(x) to within 10-8 relative or absolute error whichever is smaller.
Since:
2.0
Digamma, 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 - Argument.
Returns:
trigamma(x) to within 10-8 relative or absolute error whichever is smaller
Since:
2.0
Trigamma, digamma(double)
• #### lanczos

public static double lanczos(double x)

Returns the Lanczos approximation used to compute the gamma function. The Lanczos approximation is related to the Gamma function by the following equation

gamma(x) = sqrt(2 * pi) / x * (x + g + 0.5) ^ (x + 0.5) * exp(-x - g - 0.5) * lanczos(x),
where g is the Lanczos constant.

Parameters:
x - Argument.
Returns:
The Lanczos approximation.
Since:
3.1
Lanczos Approximation equations (1) through (5), and Paul Godfrey's Note on the computation of the convergent Lanczos complex Gamma approximation
• #### invGamma1pm1

public static double invGamma1pm1(double x)
Returns the value of 1 / Γ(1 + x) - 1 for -0.5 ≤ x ≤ 1.5. This implementation is based on the double precision implementation in the NSWC Library of Mathematics Subroutines, DGAM1.
Parameters:
x - Argument.
Returns:
The value of 1.0 / Gamma(1.0 + x) - 1.0.
Throws:
NumberIsTooSmallException - if x < -0.5
NumberIsTooLargeException - if x > 1.5
Since:
3.1
• #### logGamma1p

public static double logGamma1p(double x)
throws NumberIsTooSmallException,
NumberIsTooLargeException
Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5. This implementation is based on the double precision implementation in the NSWC Library of Mathematics Subroutines, DGMLN1.
Parameters:
x - Argument.
Returns:
The value of log(Gamma(1 + x)).
Throws:
NumberIsTooSmallException - if x < -0.5.
NumberIsTooLargeException - if x > 1.5.
Since:
3.1
• #### gamma

public static double gamma(double x)
Returns the value of Γ(x). Based on the NSWC Library of Mathematics Subroutines double precision implementation, DGAMMA.
Parameters:
x - Argument.
Returns:
the value of Gamma(x).
Since:
3.1