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A log-linear model for non-stationary time series of counts
Leucht, Anne; Neumann, Michael H. (2025): A log-linear model for non-stationary time series of counts, in: Bamberg: Otto-Friedrich-Universität, S. 709–730.
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Year of publication:
2025
Pages:
Source/Other editions:
Bernoulli, Aarhus : Bernoulli Society for Mathematical Statistics and Probability, 2025, Jg. 31, Nr. 1, S. 709–730, ISSN: 1573-9759
Year of first publication:
2025
Language:
English
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Abstract:
We propose a new model for non-stationary integer-valued time series which is particularly suitable for data with a strong trend. In contrast to popular Poisson-INGARCH models, but in line with classical GARCH models, we propose to pick the conditional distributions from nearly scale invariant families where the mean absolute value and the standard deviation are of the same order of magnitude. As an important prerequisite for applications in statistics, we prove absolute regularity of the count process with exponentially decaying coefficients.
Keywords: ; ; ; ;
Absolute regularity
count process
log-linear model
mixing
nonstationary process
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Peer Reviewed:
Yes:
International Distribution:
Yes:
Type:
Article
Activation date:
May 8, 2025
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https://fis.uni-bamberg.de/handle/uniba/105618