Multivariate Lévy-type drift change detection and mortality modeling

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<dc:creator>Krawiec, Michal </dc:creator>
<dc:creator>Palmowski, Zbigniew</dc:creator>
<dc:date>2024-04-15</dc:date>
<dc:description xml:lang="es">Sumario: 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</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/186149.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Mortalidad</dc:subject>
<dc:subject xml:lang="es">Matemática del seguro</dc:subject>
<dc:subject xml:lang="es">Modelización</dc:subject>
<dc:subject xml:lang="es">Seguros</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Multivariate Lévy-type drift change detection and mortality modeling</dc:title>
<dc:relation xml:lang="es">En: European Actuarial Journal. - Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022. - 15/04/2024 Volúmen 14 - Número 1 - abril 2024 , p. 175-203</dc:relation>
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