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Dependence on a collection of Poisson random variables

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  • Luis E. Nieto-Barajas

    (ITAM)

Abstract

We propose two novel ways of introducing dependence among Poisson counts through the use of latent variables in a three levels hierarchical model. Marginal distributions of the random variables of interest are Poisson with strict stationarity as special case. Order–p dependence is described in detail for a temporal sequence of random variables. A full Bayesian inference of the models is described and performance of the models is illustrated with a numerical analysis of maternal mortality in Mexico. Extensions to seasonal, periodic, spatial or spatio-temporal dependencies, as well as coping with overdispersion, are also discussed.

Suggested Citation

  • Luis E. Nieto-Barajas, 2022. "Dependence on a collection of Poisson random variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 21-39, March.
    • Handle: RePEc:spr:stmapp:v:31:y:2022:i:1:d:10.1007_s10260-021-00561-x
    DOI: 10.1007/s10260-021-00561-x
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    References listed on IDEAS

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