Multivariate Lévy-type drift change detection and mortality modeling

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<title>Multivariate Lévy-type drift change detection and mortality modeling</title>
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<namePart>Krawiec, Michal </namePart>
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<namePart>Palmowski, Zbigniew</namePart>
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<abstract displayLabel="Summary">In this paper we give a solution to the quickest drift change detection problem for a multivariate Lévy process consisting of both continuous (Gaussian) and jump components in the Bayesian approach. We do it for a general 0-modified continuous prior distribution of the change point as well as for a random post-change drift parameter. Classically, our criterion of optimality is based on a probability of false alarm and an expected delay of the detection, which is then reformulated in terms of a posterior probability of the change point. We find a generator of the posterior probability, which in case of general prior distribution is inhomogeneous in time</abstract>
<note type="statement of responsibility">Michal Krawiec and Zbigniew Palmowski</note>
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<topic>Mortalidad</topic>
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<topic>Matemática del seguro</topic>
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<topic>Modelización</topic>
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<topic>Seguros</topic>
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<url displayLabel="electronic resource" usage="primary display">https://link.springer.com/article/10.1007/s13385-023-00350-8</url>
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<title>European Actuarial Journal</title>
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<publisher>Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022</publisher>
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<identifier type="local">MAP20220007085</identifier>
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<text>15/04/2024 Volúmen 14 - Número 1 - abril 2024 , p. 175-203</text>
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