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On a limiting quasi-multinomial distribution

  • Nobuaki Hoshino

    (Faculty of Economics, Kanazawa University)

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    A random clustering distribution is useful for modeling count data. The present article derives a new distribution of this type from the Lagrangian Poisson distribution, based on the result that any infinitely divisible distribution over nonnegative integers produces a random clustering distribution through conditioning and a limiting argument that is equivalent to the law of small numbers. The resulting distribution is shown to be tractable. Its application is also presented.

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    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2005/2005cf361.pdf
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    Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-361.

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    Length: 16 pages
    Date of creation: Aug 2005
    Date of revision:
    Handle: RePEc:tky:fseres:2005cf361
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    1. Gupta, Pushpa L. & Gupta, Ramesh C. & Tripathi, Ram C., 1996. "Analysis of zero-adjusted count data," Computational Statistics & Data Analysis, Elsevier, vol. 23(2), pages 207-218, December.
    2. Masaaki Sibuya, 1993. "A random clustering process," Annals of the Institute of Statistical Mathematics, Springer, vol. 45(3), pages 459-465, September.
    3. Nobuaki Hoshino, 2005. "Engen's extended negative binomial model revisited," Annals of the Institute of Statistical Mathematics, Springer, vol. 57(2), pages 369-387, June.
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