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On weak dependence conditions for Poisson autoregressions

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>05/2012
<mark>Journal</mark>Statistics and Probability Letters
Issue number5
Number of pages7
Pages (from-to)942-948
Publication StatusPublished
Early online date24/01/12
<mark>Original language</mark>English


We consider generalized linear models for regression modeling of count time series. We give easily verifiable conditions for obtaining weak dependence for such models. These results enable the development of maximum likelihood inference under minimal conditions. Some examples which are useful to applications are discussed in detail.