G05SJF (PDF version)
G05 Chapter Contents
G05 Chapter Introduction
NAG Library Manual

NAG Library Routine Document


Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

G05SJF generates a vector of pseudorandom numbers taken from a gamma distribution with parameters a and b.

2  Specification

REAL (KIND=nag_wp)  A, B, X(N)

3  Description

The gamma distribution has PDF (probability density function)
fx= 1baΓa xa-1e-x/b if ​x0;  a,b>0 fx=0 otherwise.
One of three algorithms is used to generate the variates depending upon the value of a:
(i) if a<1, a switching algorithm described by Dagpunar (1988) (called G6) is used. The target distributions are f1x=caxa-1/ta and f2x=1-ce-x-t, where c=t/t+ae-t, and the switching parameter, t, is taken as 1-a. This is similar to Ahrens and Dieter's GS algorithm (see Ahrens and Dieter (1974)) in which t=1;
(ii) if a=1, the gamma distribution reduces to the exponential distribution and the method based on the logarithmic transformation of a uniform random variate is used;
(iii) if a>1, the algorithm given by Best (1978) is used. This is based on using a Student's t-distribution with two degrees of freedom as the target distribution in an envelope rejection method.
One of the initialization routines G05KFF (for a repeatable sequence if computed sequentially) or G05KGF (for a non-repeatable sequence) must be called prior to the first call to G05SJF.

4  References

Ahrens J H and Dieter U (1974) Computer methods for sampling from gamma, beta, Poisson and binomial distributions Computing 12 223–46
Best D J (1978) Letter to the Editor Appl. Statist. 27 181
Dagpunar J (1988) Principles of Random Variate Generation Oxford University Press
Hastings N A J and Peacock J B (1975) Statistical Distributions Butterworth

5  Parameters

1:     N – INTEGERInput
On entry: n, the number of pseudorandom numbers to be generated.
Constraint: N0.
2:     A – REAL (KIND=nag_wp)Input
On entry: a, the parameter of the gamma distribution.
Constraint: A>0.0.
3:     B – REAL (KIND=nag_wp)Input
On entry: b, the parameter of the gamma distribution.
Constraint: B>0.0.
4:     STATE(*) – INTEGER arrayCommunication Array
Note: the actual argument supplied must be the array STATE supplied to the initialization routines G05KFF or G05KGF.
On entry: contains information on the selected base generator and its current state.
On exit: contains updated information on the state of the generator.
5:     X(N) – REAL (KIND=nag_wp) arrayOutput
On exit: the n pseudorandom numbers from the specified gamma distribution.
6:     IFAIL – INTEGERInput/Output
On entry: IFAIL must be set to 0, -1​ or ​1. If you are unfamiliar with this parameter you should refer to Section 3.3 in the Essential Introduction for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1​ or ​1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is 0. When the value -1​ or ​1 is used it is essential to test the value of IFAIL on exit.
On exit: IFAIL=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6  Error Indicators and Warnings

If on entry IFAIL=0 or -1, explanatory error messages are output on the current error message unit (as defined by X04AAF).
Errors or warnings detected by the routine:
On entry, N<0.
On entry, A0.0.
On entry, B0.0.
On entry,STATE vector was not initialized or has been corrupted.

7  Accuracy

Not applicable.

8  Further Comments


9  Example

This example prints a set of five pseudorandom numbers from a gamma distribution with parameters a=5.0 and b=1.0, generated by a single call to G05SJF, after initialization by G05KFF.

9.1  Program Text

Program Text (g05sjfe.f90)

9.2  Program Data

Program Data (g05sjfe.d)

9.3  Program Results

Program Results (g05sjfe.r)

G05SJF (PDF version)
G05 Chapter Contents
G05 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2012