Abstract
Since, in statistics, it is a key task to pick the best out of a set of models to describe a given data set, the verification of this choice should be done with certain care. Commonly, model selection is done based on an information criterion, followed by subsequent checks of model adequacy. In this paper, further, more specific criteria for counts are proposed to validate the selected model. The procedure is exemplified by a count data application.
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Acknowledgements
The author is grateful to the referee and to Prof. Dr. Christian H. Weiß (Helmut Schmidt University) for their useful comments, which greatly improved this article.
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Homburg, A. (2019). Criteria to Validate Count Data Model Selection. In: Steland, A., Rafajłowicz, E., Okhrin, O. (eds) Stochastic Models, Statistics and Their Applications. SMSA 2019. Springer Proceedings in Mathematics & Statistics, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-28665-1_32
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DOI: https://doi.org/10.1007/978-3-030-28665-1_32
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