Multivariate Lévy-type drift change detection and mortality modeling

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      <subfield code="a">Krawiec, Michal </subfield>
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      <subfield code="a">Multivariate Lévy-type drift change detection and mortality modeling</subfield>
      <subfield code="c">Michal Krawiec and Zbigniew Palmowski</subfield>
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      <subfield code="a">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</subfield>
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      <subfield code="a">Matemática del seguro</subfield>
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      <subfield code="a">Modelización</subfield>
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      <subfield code="a">Palmowski, Zbigniew</subfield>
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      <subfield code="w">MAP20220007085</subfield>
      <subfield code="g">15/04/2024 Volúmen 14 - Número 1 - abril 2024 , p. 175-203</subfield>
      <subfield code="t">European Actuarial Journal</subfield>
      <subfield code="d">Cham, Switzerland  : Springer Nature Switzerland AG,  2021-2022</subfield>
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      <subfield code="u">https://link.springer.com/article/10.1007/s13385-023-00350-8</subfield>
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