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Models for zero-inflated count data using the Neyman type A distribution

Centre for Mathematics and its Applications, School of Mathematical Sciences, Australian National University, Canberra, Australia, melissa.dobbie{at}cmis.csiro.au

Alan H Welsh

Faculty of Mathematical Studies, The University of Southampton, Highfield, Southampton, UK

We explore the possibility of modelling zero-inflated count data using the Neyman type A distribution. We extend three parameterizations of the Neyman type A distribution to allow their parameters to depend on covariates. We develop models which relate counts of Leadbeater’s possum to various habitat variables to illustrate the methodology. Half-normal plots are constructed for each model to explore the quality of the fit. We then formally compare the Neyman type A models using the method of Cox to test non-nested hypotheses. Finally, we compare each of the Neyman type A models with a model from a competing family, the conditional Poisson model.

Key Words: contagious distributions • covariate adjustment • Neyman type A distribution • non-nested hypothesis • parameterization • zero-inflated counts

Statistical Modelling, Vol. 1, No. 1, 65-80 (2001)
DOI: 10.1177/1471082X0100100106


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