Rejection-Inversion to Generate Variates from Monotone Discrete Distributions

Hörmann, Wolfgang and Derflinger, Gerhard (1996) Rejection-Inversion to Generate Variates from Monotone Discrete Distributions. Preprint Series / Department of Applied Statistics and Data Processing, 15. Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, Vienna.


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For discrete distributions a variant of rejection from a continuous hat function is presented. The main advantage of the new method, called rejection-inversion, is that no extra uniform random number to decide between acceptance and rejection is required which means that the expected number of uniform variates required is halved. Using rejection-inversion and a squeeze, a simple universal method for a large class of monotone discrete distributions is developed. It can be used to generate variates from the tails of most standard discrete distributions. Rejection-inversion applied to the Zipf (or zeta) distribution results in algorithms that are short and simple and at least twice as fast as the fastest methods suggested in the literature. (author's abstract)

Item Type: Paper
Additional Information: published in: ACM Transactions on Mathematical Software 6(3), 1996, pp. 169-184.
Keywords: random number generation / rejection method / Zipf distribution / tail of Poisson distribution / universal algorithm / T-concave
Classification Codes: MSC 65C10, CCS G.3
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 10 Jul 2006 11:20
Last Modified: 22 Oct 2019 00:41
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