Compound Poisson INAR(1) processes: stochastic properties and testing for overdispersion
The compound Poisson INAR(1) model for time series of overdispersed counts is considered. For such CPINAR(1) processes, explicit results are derived for joint moments, for the k-step-ahead distribution as well as for the stationary distribution. It is shown that a CPINAR(1) process is strongly mixin...
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| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
17 March 2014
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| In: |
Computational statistics & data analysis
Year: 2014, Jahrgang: 77, Pages: 267-284 |
| DOI: | 10.1016/j.csda.2014.03.005 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1016/j.csda.2014.03.005 Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S0167947314000826 
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| Verfasserangaben: | Sebastian Schweer, Christian H. Weiß |
| Zusammenfassung: | The compound Poisson INAR(1) model for time series of overdispersed counts is considered. For such CPINAR(1) processes, explicit results are derived for joint moments, for the k-step-ahead distribution as well as for the stationary distribution. It is shown that a CPINAR(1) process is strongly mixing with exponentially decreasing weights. This result is utilized to design a test for overdispersion in INAR(1) processes and to derive its asymptotic power function. An application of our results to a real-data example and a study of the finite-sample performance of the test are presented. |
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| Beschreibung: | Gesehen am 29.05.2018 |
| Beschreibung: | Online Resource |
| DOI: | 10.1016/j.csda.2014.03.005 |