Modelling interventions in INGARCH processes

Liboschik, T. and Kerschke, P. and Fokianos, K. and Fried, R. (2016) Modelling interventions in INGARCH processes. International Journal of Computer Mathematics, 93 (4). pp. 640-657.

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Abstract

We study different approaches for modelling intervention effects in time series of counts, focusing on the so-called integer-valued GARCH models. A previous study treated a model where an intervention affects the non-observable underlying mean process at the time point of its occurrence and additionally the whole process thereafter via its dynamics. As an alternative, we consider a model where an intervention directly affects the observation at its occurrence, but not the underlying mean, and then also enters the dynamics of the process. While the former definition describes an internal change of the system, the latter can be understood as an external effect on the observations due to e.g. immigration. For our alternative model we develop conditional likelihood estimation and, based on this, tests and detection procedures for intervention effects. Both models are compared analytically and using simulated and real data examples. We study the effect of model misspecification and computational issues.

Item Type:
Journal Article
Journal or Publication Title:
International Journal of Computer Mathematics
Subjects:
?? change-point detectiongeneralized linear modelslevel shiftsoutlierstime series of counts ??
ID Code:
127750
Deposited By:
Deposited On:
26 Sep 2018 08:18
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 18:22