Estimating the parameters of a seasonal Markov-modulated Poisson process

Abstract : We present a new model of counting processes in insurance. The process is 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 simulation study.
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https://hal.archives-ouvertes.fr/hal-00965279
Contributor : Gilles Stupfler <>
Submitted on : Monday, March 24, 2014 - 10:19:42 PM
Last modification on : Thursday, May 3, 2018 - 9:42:42 AM
Long-term archiving on : Tuesday, June 24, 2014 - 12:57:46 PM

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Armelle Guillou, Stéphane Loisel, Gilles Stupfler. Estimating the parameters of a seasonal Markov-modulated Poisson process. 2014. ⟨hal-00965279v1⟩

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