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Zero inflated Poisson distribution in equidispersed data with excessive zeros

Author Affiliations

  • 1University of Botswana, Gaborone, Botswana
  • 2University of Botswana, Gaborone, Botswana

Res. J. Mathematical & Statistical Sci., Volume 8, Issue (1), Pages 31-34, January,12 (2020)


From the literature, choosing the right model when the dependent variable is a count outcome remains a problem in literature. For count outcome variable with overdispersion due to excessive zero counts (zero inflation), Zero Inflated distributions such as Zero Inflated Poisson/Negative Binomial are usually considered to find better fitting models. Moreover, numerous studies suggested that if the data is characterized by equidispersion with signs of zero inflation, Zero Inflated Poisson (ZIP) distribution should be applied. Therefore, the aim of this paper is to investigate if ZIP distribution should substitute standard Poisson distribution if there are signs of zero inflation in equidispersed data. Equidispersed simulated and real life datasets with signs of zero inflation were used for the analysis. Evidence of equidispersion and zero inflation were tested and goodness-of-fit tests for both Poisson and ZIP distributions were obtained. Results revealed that for an equidispersed data with signs of zero inflation, standard Poisson performed better than ZIP distribution.


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