Options
Mixing properties of non-stationary INGARCH(1, 1) processes
Doukhan, Paul; Leucht, Anne; Neumann, Michael H. (2022): Mixing properties of non-stationary INGARCH(1, 1) processes, in: Bamberg: Otto-Friedrich-Universität, S. 663–688.
Faculty/Chair:
Author:
Publisher Information:
Year of publication:
2022
Pages:
Source/Other editions:
Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability. - (2021), Version: April 8, 2021, S. 663–688. - ISSN: 1573-9759
Year of first publication:
2021
Language:
English
Licence:
Abstract:
We derive mixing properties for a broad class of Poisson count time series satisfying a certain contraction condition. Using specific coupling techniques, we prove absolute regularity at a geometric rate not only for stationary Poisson-GARCH processes but also for models with an explosive trend. We provide easily verifiable sufficient conditions for absolute regularity for a variety of models including classical (log-)linear models. Finally, we illustrate the practical use of our results for hypothesis testing.
GND Keywords: ; ; ; ;
Poisson-Prozess
GARCH-Prozess
Lineares Modell
Regelmäßigkeit
Zeitreihe
Keywords: ;
Absolute regularity
INGARCH
DDC Classification:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Type:
Article
Activation date:
August 24, 2022
Permalink
https://fis.uni-bamberg.de/handle/uniba/55004