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A new bivariate generalized Poisson distribution

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  • Felix Famoye

Abstract

In this paper, a new bivariate generalized Poisson distribution (GPD) that allows any type of correlation is defined and studied. The marginal distributions of the bivariate model are the univariate GPDs. The parameters of the bivariate distribution are estimated by using the moment and maximum likelihood methods. Some test statistics are discussed and one numerical data set is used to illustrate the applications of the bivariate model.

Suggested Citation

  • Felix Famoye, 2010. "A new bivariate generalized Poisson distribution," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(1), pages 112-124, February.
    • Handle: RePEc:bla:stanee:v:64:y:2010:i:1:p:112-124
    DOI: 10.1111/j.1467-9574.2009.00446.x
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    References listed on IDEAS

    as
    1. Felix Famoye & P. Consul, 1995. "Bivariate generalized Poisson distribution with some applications," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 42(1), pages 127-138, December.
    2. Rainer Winkelmann, 2008. "Econometric Analysis of Count Data," Springer Books, Springer, edition 0, number 978-3-540-78389-3, December.
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    Cited by:

    1. Vera Hofer & Johannes Leitner, 2012. "A bivariate Sarmanov regression model for count data with generalised Poisson marginals," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(12), pages 2599-2617, August.
    2. Marek Patrice & Ťoupal Tomáš & Šedivá Blanka, 2014. "Modeling and prediction of ice hockey match results," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(3), pages 1-9, September.
    3. Lluís Bermúdez & Dimitris Karlis, 2021. "Multivariate INAR(1) Regression Models Based on the Sarmanov Distribution," Mathematics, MDPI, vol. 9(5), pages 1-13, March.
    4. Sarni Maniar Berliana & Purhadi & Sutikno & Santi Puteri Rahayu, 2020. "Parameter Estimation and Hypothesis Testing of Geographically Weighted Multivariate Generalized Poisson Regression," Mathematics, MDPI, vol. 8(9), pages 1-14, September.
    5. Kennedy Ndue & Melese Mulu Baylie & Pál Goda, 2023. "Determinants of Rural Households’ Intensity of Flood Adaptation in the Fogera Rice Plain, Ethiopia: Evidence from Generalised Poisson Regression," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    6. Tzougas, George & di Cerchiara, Alice Pignatelli, 2021. "Bivariate mixed Poisson regression models with varying dispersion," LSE Research Online Documents on Economics 114327, London School of Economics and Political Science, LSE Library.

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