Modelling heavy-tailed count data using a generalised Poisson-inverse Gaussian family

Rong Zhu and Harry Joe

Statistics & Probability Letters, 2009, vol. 79, issue 15, 1695-1703

Abstract: We generalise the Poisson-inverse Gaussian distribution to a three-parameter family, which includes the Poisson and discrete stable distributions as boundary cases. It is flexible in modelling count data sets with different tail heaviness. Although the family only has a closed-form probability generating function, a recursive method is developed for statistical inferences based on the likelihood. As an example, this new family is applied to data sets of citation counts of published articles.

Date: 2009
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Citations: View citations in EconPapers (9)

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