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Journal Articles Statistical Methodology Year : 2015

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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Dates and versions

hal-00965279 , version 1 (24-03-2014)
hal-00965279 , version 2 (24-02-2017)

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Cite

Armelle Guillou, Stéphane Loisel, Gilles Stupfler. Estimating the parameters of a seasonal Markov-modulated Poisson process. Statistical Methodology, 2015, 26, pp.103-123. ⟨10.1016/j.stamet.2015.04.003⟩. ⟨hal-00965279v2⟩
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