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On infinitely divisible multivariate gamma distributions

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  • Stephen G. Walker

Abstract

We provide an explicit construction of variables from a bivariate gamma distribution which is infinitely divisible. These distributions are currently only known through their (complicated) density functions or moment generating functions. The sampling construction uses independent gamma and Poisson random variables and sheds further light on these distributions and their infinitely divisible property. The extension to multivariate gamma infinitely divisible variables is also provided, as well as a negative binomial case.

Suggested Citation

  • Stephen G. Walker, 2023. "On infinitely divisible multivariate gamma distributions," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(13), pages 4484-4490, July.
    • Handle: RePEc:taf:lstaxx:v:52:y:2023:i:13:p:4484-4490
    DOI: 10.1080/03610926.2021.1995431
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    Cited by:

    1. Na Young Yoo & Ji Hwan Cha, 2024. "General classes of bivariate distributions for modeling data with common observations," Statistical Papers, Springer, vol. 65(8), pages 5219-5238, October.

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