A stochastic network approach to test and checkout
Proceedings of the fourth annual conference on Applications of simulation
Generating beta variates with nonintegral shape parameters
Communications of the ACM
Computer generation of gamma random variables
Communications of the ACM
Computer generation of gamma random variables—II
Communications of the ACM
Sampling from the gamma distribution on a computer
Communications of the ACM
A survey of methods for sampling from the gamma distribution
WSC '78 Proceedings of the 10th conference on Winter simulation - Volume 1
Speech enhancement by map spectral amplitude estimation using a super-Gaussian speech model
EURASIP Journal on Applied Signal Processing
Application of the simulation with a spreadsheet to Queueing theory
MATH'05 Proceedings of the 8th WSEAS International Conference on Applied Mathematics
On the moment-determinance and random mixture of Nakagami-m variates
IEEE Transactions on Communications
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When the shape parameter, &agr;, is integral, generating gamma random variables with a digital computer is straightforward. There is no simple method for generating gamma random variates with non-integral shape parameters. A common procedure is to approximately generate such random variables by use of the so-called probability switch method. Another procedure, which is exact, is due to Jöhnk. This paper presents a rejection method for exactly generating gamma random variables when &agr; is greater than 1. The efficiency of the rejection method is shown to be better than the efficiency of Jöhnk's method. The paper concludes that when &agr; is non-integral the following mix of procedures yields the best combination of accuracy and efficiency: (1) when &agr; is less than 1, use Jöhnk's method; (2) when 1 is less than &agr; and &agr; is less than 5, use the rejection method; (3) when &agr; is greater than 5, use the probability switch method.