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Estimating the parameters of a seasonal Markov-modulated Poisson process

Abstract : Motivated by seasonality and regime-switching features of some insurance claim counting processes, we study the statistical analysis of a Markov-modulated Poisson process featuring seasonality. We prove the strong consistency and the asymptotic normality of a maximum split-time likelihood estimator of the parameters of this model, and present an algorithm to compute it in practice. The method is illustrated on a small simulation study and a real data analysis.
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Submitted on : Friday, February 3, 2017 - 11:59:04 PM
Last modification on : Wednesday, August 5, 2020 - 3:12:33 AM

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Armelle Guillou, Stéphane Loisel, Gilles Stupfler. Estimating the parameters of a seasonal Markov-modulated Poisson process. Statistical Methodology, Elsevier, 2015, 26, pp.103--123. ⟨10.1016/j.stamet.2015.04.003⟩. ⟨hal-01456131⟩

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