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On count time series prediction

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<mark>Journal publication date</mark>2015
<mark>Journal</mark>Journal of Statistical Computation and Simulation
Issue number2
Number of pages17
Pages (from-to)357-373
Publication statusPublished
Early online date1/08/13
Original languageEnglish


We consider the problem of assessing prediction for count time series based on either the Poisson distribution or the negative binomial distribution. By a suitable parametrization we employ both distributions with the same mean. We regress the mean on its past values and the values of the response and after obtaining consistent estimators of the regression parameters, regardless of the response distribution, we employ different criteria to study the prediction problem. We show by simulation and data examples that scoring rules and diagnostic graphs that have been proposed for independent but not identically distributed data can be adapted in the setting of count dependent data.