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The Computer Generation of Poisson Random Variables

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  • A. C. Atkinson

Abstract

A comparison is made of methods of generating samples on a computer from the Poisson distribution. The well‐known methods of counting the number of occurrences in a Poisson process and of sequentially searching through a table of cumulative probabilities have the disadvantage that the time required increases with the Poisson parameter μ. For fixed μ two modified search procedures are described which remain fast as μ increases. If μ. varies from sample to sample the modified search procedures are not directly applicable. But fast methods can be found which use combinations of either modified search method and are appreciably faster than rejection methods.

Suggested Citation

  • A. C. Atkinson, 1979. "The Computer Generation of Poisson Random Variables," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(1), pages 29-35, March.
    • Handle: RePEc:bla:jorssc:v:28:y:1979:i:1:p:29-35
    DOI: 10.2307/2346807
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    Cited by:

    1. Cheng, Ching-Wei & Hung, Ying-Chao & Balakrishnan, Narayanaswamy, 2014. "Generating beta random numbers and Dirichlet random vectors in R: The package rBeta2009," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1011-1020.
    2. Yan, Xi Steven & Robb, David J. & Silver, Edward A., 2009. "Inventory performance under pack size constraints and spatially-correlated demand," International Journal of Production Economics, Elsevier, vol. 117(2), pages 330-337, February.
    3. Ong, S.H. & Lee, Wen-Jau, 2008. "Computer generation of negative binomial variates by envelope rejection," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4175-4183, May.
    4. ALBANO, Gian Luigi & JOUNEAU, Fréféric, 1998. "A Bayesian approach to the econometrics of first-price auctions," LIDAM Discussion Papers CORE 1998031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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