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On a limiting quasi-multinomial distribution

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  • Nobuaki Hoshino

    (Faculty of Economics, Kanazawa University)

Abstract

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.

Suggested Citation

  • Nobuaki Hoshino, 2005. "On a limiting quasi-multinomial distribution," CIRJE F-Series CIRJE-F-361, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2005cf361
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    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2005/2005cf361.pdf
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    References listed on IDEAS

    as
    1. Masaaki Sibuya, 1993. "A random clustering process," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(3), pages 459-465, September.
    2. Nobuaki Hoshino, 2005. "Engen's extended negative binomial model revisited," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(2), pages 369-387, June.
    3. 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.
    4. Hoshino, Nobuaki & Akimichi Takemura, 1998. ""On the Relation between Logarithmic Series Model and Other Superpopulation Models Useful for Microdata Disclosure Risk Assessment"," CIRJE F-Series 98-F-7, CIRJE, Faculty of Economics, University of Tokyo.
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