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Accurate estimation for extra-Poisson variability assuming random effect models

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  • Ricardo Puziol de Oliveira
  • Jorge Alberto Achcar

Abstract

In this study, the components of extra-Poisson variability are estimated assuming random effect models under a Bayesian approach. A standard existing methodology to estimate extra-Poisson variability assumes a negative binomial distribution. The obtained results show that using the proposed random effect model it is possible to get more accurate estimates for the extra-Poisson variability components when compared to the use of a negative binomial distribution where it is possible to estimate only one component of extra-Poisson variability. Some illustrative examples are introduced considering real data sets.

Suggested Citation

  • Ricardo Puziol de Oliveira & Jorge Alberto Achcar, 2021. "Accurate estimation for extra-Poisson variability assuming random effect models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 48(16), pages 2982-3001, December.
    • Handle: RePEc:taf:japsta:v:48:y:2021:i:16:p:2982-3001
    DOI: 10.1080/02664763.2020.1789075
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