Arbeitspapier
Interventions in ingarch processes
We study the problem of intervention effects generating various types of outliers in a linear count time series model. This model belongs to the class of observation driven models and extends the class of Gaussian linear time series models within the exponential family framework. Studies about effects of covariates and interventions for count time series models have largely fallen behind due to the fact that the underlying process, whose behavior determines the dynamics of the observed process, is not observed. We suggest a computationally feasible approach to these problems, focusing especially on the detection and estimation of sudden shifts and outliers. To identify successfully such unusual events we employ the maximum of score tests, whose critical values in finite samples are determined by parametric bootstrap. The usefulness of the proposed methods is illustrated using simulated and real data examples.
- Language
-
Englisch
- Bibliographic citation
-
Series: Technical Report ; No. 2009,11
- Subject
-
parametric bootstrap
generalized linear models
observation driven models
level shifts
transient shifts
outliers
Zeitreihenanalyse
Zähldatenmodell
Theorie
- Event
-
Geistige Schöpfung
- (who)
-
Fokianos, Konstantions
Fried, Roland
- Event
-
Veröffentlichung
- (who)
-
Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
-
Dortmund
- (when)
-
2009
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Fokianos, Konstantions
- Fried, Roland
- Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2009
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