On count time series prediction

Christou, V. and Fokianos, K. (2015) On count time series prediction. Journal of Statistical Computation and Simulation, 85 (2). pp. 357-373. ISSN 0094-9655

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Abstract

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.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Statistical Computation and Simulation
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2611
Subjects:
?? calibrationpredictionprobability integral transformation plotquasi-likelihoodscoring rulessharpnessmodelling and simulationapplied mathematicsstatistics and probabilitystatistics, probability and uncertainty ??
ID Code:
127754
Deposited By:
Deposited On:
26 Sep 2018 07:52
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 18:22