On Outliers and Interventions in Count Time Series following GLMs

  • Roland Fried University of Dortmund
  • Tobias Liboschik University of Dortmund
  • Hanan Elsaied
  • Stella Kitromilidou University of Cyprus
  • Konstantinos Fokianos


We discuss the analysis of count time series following generalised linear models in the presence of outliers and intervention effects. Different modifications of such models are formulated which allow to incorporate, detect and to a certain degree distinguish extraordinary events (interventions) of different types in count time series retrospectively. An outlook on extensions to the problem of robust parameter estimation, identification of the model orders by robust estimation of autocorrelations and partial autocorrelations, and online surveillance by sequential testing for outlyingness is provided. 

How to Cite
Fried, R., Liboschik, T., Elsaied, H., Kitromilidou, S., & Fokianos, K. (2014). On Outliers and Interventions in Count Time Series following GLMs. Austrian Journal of Statistics, 43(3), 181-193. https://doi.org/https://doi.org/10.17713/ajs.v43i3.30