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On modelling overdispersion of counts

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  • K. Poortema

Abstract

For counts it often occurs that the observed variance exceeds the nominal variance of the claimed binomial, multinomial or Poisson distributions. We study how models can be extended to cope with this phenomenon: a survey of literature is given. We focus on modelling, not on estimation or testing statistical hypotheses. The attention is restricted to independent observations.

Suggested Citation

  • K. Poortema, 1999. "On modelling overdispersion of counts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 53(1), pages 5-20, March.
    • Handle: RePEc:bla:stanee:v:53:y:1999:i:1:p:5-20
    DOI: 10.1111/1467-9574.00094
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    Cited by:

    1. Rodríguez-Avi, J. & Conde-Sánchez, A. & Sáez-Castillo, A.J. & Olmo-Jiménez, M.J. & Martínez-Rodríguez, A.M., 2009. "A generalized Waring regression model for count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3717-3725, August.
    2. Willem Albers, 2011. "Control charts for health care monitoring under overdispersion," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 74(1), pages 67-83, July.
    3. José Rodríguez-Avi & María José Olmo-Jiménez, 2017. "A regression model for overdispersed data without too many zeros," Statistical Papers, Springer, vol. 58(3), pages 749-773, September.
    4. Christian H. Weiß, 2011. "Detecting mean increases in Poisson INAR(1) processes with EWMA control charts," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 383-398, September.
    5. Rob Eisinga, 2009. "The beta‐binomial convolution model for 2×2 tables with missing cell counts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(1), pages 24-42, February.
    6. Corsini, Noemi & Viroli, Cinzia, 2022. "Dealing with overdispersion in multivariate count data," Computational Statistics & Data Analysis, Elsevier, vol. 170(C).

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