Inference for nonstationary time series of counts with application to change-point problems

@article{Kengne2022InferenceFN,
title={Inference for nonstationary time series of counts with application to change-point problems},
author={William Kengne and Isidore S'eraphin Ngongo},
journal={Annals of the Institute of Statistical Mathematics},
year={2022},
volume={74},
pages={801-835}
}
• Published 2 May 2020
• Mathematics
• Annals of the Institute of Statistical Mathematics
We consider an integer-valued time series $$(Y_t)_{t\in {\mathbb {Z}}}$$ ( Y t ) t ∈ Z where the model after a time $$k^*$$ k ∗ is Poisson autoregressive with the conditional mean that depends on a parameter $$\theta ^*\in \varTheta \subset {\mathbb {R}}^d$$ θ ∗ ∈ Θ ⊂ R d . The structure of the process before $$k^*$$ k ∗ is unknown; it could be any other integer-valued process, that is, $$(Y_t)_{t\in {\mathbb {Z}}}$$ ( Y t ) t ∈ Z could be nonstationary. It is established that the maximum…
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