Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
416551 | Computational Statistics & Data Analysis | 2009 | 12 Pages |
Abstract
A new methodology to detect zero-inflation and overdispersion is proposed, based on a comparison of the expected sample extremes among convexly ordered distributions. The method is very flexible and includes tests for the proportion of structural zeros in zero-inflated models, tests to distinguish between two ordered parametric families and a new general test to detect overdispersion. The performance of the proposed tests is evaluated via some simulation studies. For the well-known fetal lamb data, the conclusion is that the zero-inflated Poisson model should be rejected against other more disperse models, but the negative binomial model cannot be rejected.
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Physical Sciences and Engineering
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Computational Theory and Mathematics
Authors
A. Baíllo, J.R. Berrendero, J. Cárcamo,