B0372
Title: Testing for the generalized Poisson-inverse Gaussian distribution
Authors: Apostolos Batsidis - University of Ioannina (Greece) [presenting]
Maria Dolores Jimenez-Gamero - Universidad de Sevilla (Spain)
Virtudes Alba-Fernandez - University of Jaen (Spain)
Abstract: The generalized Poisson inverse Gaussian (GPIG) family is a flexible family of distributions, useful for modeling count data with different tail heaviness. The probability generating function (PGF) of the GPIP family is the unique PGF satisfying certain differential equation. This property leads us to propose a new goodness-of-fit test for the GPIP family. It is shown that the test is consistent against fixed alternatives. The null distribution of the test statistic can be consistently approximated by means of a parametric and a weighted bootstrap. The finite sample performance of the proposed test is investigated by means of a simulation study, where the goodness of the proposed approximations is numerically studied.
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