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A Simple Gamma Random Number Generator for Arbitrary Shape Parameters

Author

Listed:
  • Hisashi Tanizaki

    (Graduate School of Economics, Kobe University)

Abstract

This paper proposes an improved gamma random generator. In the past, a lot of gamma random number generators have been proposed, and depending on a shape parameter (say, alpha) they are roughly classified into two cases: (i) alpha lies on the interval (0,1) and (ii) alpha is greater than 1, where alpha=1 can be included in either case. In addition, Cheng and Feast (1980) extended the gamma random number generator in the case where alpha is greater than 1/n, where n denotes an arbitrary positive number. Taking n as a decreasing function of alpha, in this paper we propose a simple gamma random number generator with shape parameter alpha greater than zero. The proposed algorithm is very simple and shows quite good performance.

Suggested Citation

  • Hisashi Tanizaki, 2008. "A Simple Gamma Random Number Generator for Arbitrary Shape Parameters," Economics Bulletin, AccessEcon, vol. 3(7), pages 1-10.
    • Handle: RePEc:ebl:ecbull:eb-07c10012
    as

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    References listed on IDEAS

    as
    1. R. C. H. Cheng, 1977. "The Generation of Gamma Variables with Non‐Integral Shape Parameter," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 26(1), pages 71-75, March.
    2. R. C. H. Cheng & G. M. Feast, 1979. "Some Simple Gamma Variate Generators," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(3), pages 290-295, November.
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    Citations

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    Cited by:

    1. Chuanhai Liu & Ryan Martin & Nick Syring, 2017. "Efficient simulation from a gamma distribution with small shape parameter," Computational Statistics, Springer, vol. 32(4), pages 1767-1775, December.
    2. Devroye, Luc, 2021. "Random variate generation for the truncated negative gamma distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 181(C), pages 51-56.
    3. Kenichiro Shiraya & Cong Wang & Akira Yamazaki, 2021. "A general control variate method for time-changed Lévy processes: An application to options pricing," CARF F-Series CARF-F-499, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    4. Joshi, Mark S. & Zhu, Dan, 2016. "An exact method for the sensitivity analysis of systems simulated by rejection techniques," European Journal of Operational Research, Elsevier, vol. 254(3), pages 875-888.

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    More about this item

    Keywords

    Gamma Random Variable;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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