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On weak dependence conditions for Poisson autoregressions. (English) Zbl 1241.62109

Stat. Probab. Lett. 82, No. 5, 942-948 (2012); correction ibid. 83, No. 8, 1926-1927 (2013).
Summary: 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.

MSC:

62J12 Generalized linear models (logistic models)
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62M09 Non-Markovian processes: estimation
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