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Simulating Bessel random variables

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  • Devroye, Luc
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    Abstract

    In this paper, we discuss efficient exact random variate generation for the Bessel distribution. The expected time of the algorithm is uniformly bounded over all choices of the parameters, and the algorithm avoids any computation of Bessel functions or Bessel ratios.

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    File URL: http://www.sciencedirect.com/science/article/B6V1D-45574RX-2/2/cd5b22ecd2fce0c49888666379733b70
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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 57 (2002)
    Issue (Month): 3 (April)
    Pages: 249-257

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    Handle: RePEc:eee:stapro:v:57:y:2002:i:3:p:249-257

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    Related research

    Keywords: Random variate generation Bessel distribution Rejection method Simulation Monte Carlo method Expected time analysis Probability inequalities;

    References

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    1. Lin Yuan & John Kalbfleisch, 2000. "On the Bessel Distribution and Related Problems," Annals of the Institute of Statistical Mathematics, Springer, vol. 52(3), pages 438-447, September.
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    Cited by:
    1. Paul Glasserman & Kyoung-Kuk Kim, 2011. "Gamma expansion of the Heston stochastic volatility model," Finance and Stochastics, Springer, vol. 15(2), pages 267-296, June.
    2. Akihiro Tanabe & Kenji Fukumizu & Shigeyuki Oba & Takashi Takenouchi & Shin Ishii, 2007. "Parameter estimation for von Mises–Fisher distributions," Computational Statistics, Springer, vol. 22(1), pages 145-157, April.
    3. Fotopoulos, Stergios B. & Jandhyala, Venkata K., 2004. "Bessel inequalities with applications to conditional log returns under GIG scale mixtures of normal vectors," Statistics & Probability Letters, Elsevier, vol. 66(2), pages 117-125, January.

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