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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 & 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.
    2. 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.
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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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