New generators of normal and Poisson deviates based on the transformed rejection method

Hörmann, Wolfgang (1992) New generators of normal and Poisson deviates based on the transformed rejection method. Preprint Series / Department of Applied Statistics and Data Processing, 4. Institut für Statistik und Mathematik, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, Vienna.


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The transformed rejection method uses inversion to sample from the dominating density of a rejection algorithm. But in contrast to the usual method it is enough to know the inverse distribution function F^(-1)(x) of the dominating density. This idea can be applied to various continuous (e.g. normal, Cauchy and exponential) and discrete (e.g. binomial and Poisson) distributions with high acceptance probabilities. The resulting algorithms are short, simple and fast. Even more important is the fact that the quality of the method when used in combination with a linear congruential uniform generator is high compared with the quality of the ratio of uniforms method. In addition transformed rejection can be easily employed for correlation induction. (author's abstract)

Item Type: Paper
Additional Information: In: Hansmann K.-W. et al, editors, Operations Research Proceedings 1992, pp. 334-341, Berlin: Springer 1993
Keywords: random variate generation / rejection method
Classification Codes: MSC 65C10, CR G.3
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 03 May 2004 19:57
Last Modified: 22 Oct 2019 00:40


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