nag_rand_gamma (g05sjc) (PDF version)
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g05 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_rand_gamma (g05sjc)

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_rand_gamma (g05sjc) generates a vector of pseudorandom numbers taken from a gamma distribution with parameters a and b.

2  Specification

#include <nag.h>
#include <nagg05.h>
void  nag_rand_gamma (Integer n, double a, double b, Integer state[], double x[], NagError *fail)

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 argument, 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 functions nag_rand_init_repeatable (g05kfc) (for a repeatable sequence if computed sequentially) or nag_rand_init_nonrepeatable (g05kgc) (for a non-repeatable sequence) must be called prior to the first call to nag_rand_gamma (g05sjc).

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  Arguments

1:     nIntegerInput
On entry: n, the number of pseudorandom numbers to be generated.
Constraint: n0.
2:     adoubleInput
On entry: a, the parameter of the gamma distribution.
Constraint: a>0.0.
3:     bdoubleInput
On entry: b, the parameter of the gamma distribution.
Constraint: b>0.0.
4:     state[dim]IntegerCommunication Array
Note: the dimension, dim, of this array is dictated by the requirements of associated functions that must have been previously called. This array MUST be the same array passed as argument state in the previous call to nag_rand_init_repeatable (g05kfc) or nag_rand_init_nonrepeatable (g05kgc).
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]doubleOutput
On exit: the n pseudorandom numbers from the specified gamma distribution.
6:     failNagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

On entry, argument value had an illegal value.
On entry, n=value.
Constraint: n0.
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
On entry, state vector has been corrupted or not initialized.
On entry, a=value.
Constraint: a>0.0.
On entry, b=value.
Constraint: b>0.0.

7  Accuracy

Not applicable.

8  Parallelism and Performance

nag_rand_gamma (g05sjc) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
Please consult the Users' Note for your implementation for any additional implementation-specific information.

9  Further Comments


10  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 nag_rand_gamma (g05sjc), after initialization by nag_rand_init_repeatable (g05kfc).

10.1  Program Text

Program Text (g05sjce.c)

10.2  Program Data


10.3  Program Results

Program Results (g05sjce.r)

nag_rand_gamma (g05sjc) (PDF version)
g05 Chapter Contents
g05 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2014