Artikel
Likelihood inference for generalized integer autoregressive time series models
For modeling count time series data, one class of models is generalized integer autoregressive of order p based on thinning operators. It is shown how numerical maximum likelihood estimation is possible by inverting the probability generating function of the conditional distribution of an observation given the past p observations. Two data examples are included and show that thinning operators based on compounding can substantially improve the model fit compared with the commonly used binomial thinning operator.
- Sprache
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Englisch
- Erschienen in
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Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 7 ; Year: 2019 ; Issue: 4 ; Pages: 1-13 ; Basel: MDPI
- Klassifikation
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Wirtschaft
- Thema
-
binomial thinning
compounding operation
count time series
self-generalized property
thinning operators
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Joe, Harry
- Ereignis
-
Veröffentlichung
- (wer)
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MDPI
- (wo)
-
Basel
- (wann)
-
2019
- DOI
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doi:10.3390/econometrics7040043
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Joe, Harry
- MDPI
Entstanden
- 2019
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