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Article Dans Une Revue Journal of Time Series Analysis Année : 2021

Necessary and sufficient conditions for the identifiability of observation-driven models

Résumé

In this contribution we are interested in proving that a given observation-driven model is identifiable. In the case of a GARCH(p, q) model, a simple sufficient condition has been established in [1] for showing the consistency of the quasi-maximum likelihood estimator. It turns out that this condition applies for a much larger class of observation-driven models, that we call the class of linearly observation-driven models. This class includes standard integer valued observation-driven time series, such as the log-linear Poisson GARCH or the NBIN-GARCH models.
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Dates et versions

hal-02088860 , version 1 (04-04-2019)
hal-02088860 , version 2 (30-04-2020)
hal-02088860 , version 3 (08-09-2020)

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Randal Douc, François Roueff, Tepmony Sim. Necessary and sufficient conditions for the identifiability of observation-driven models. Journal of Time Series Analysis, 2021, 42 (2), pp.140-160. ⟨10.1111/jtsa.12559⟩. ⟨hal-02088860v3⟩
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