Multivariate Lévy-type drift change detection and mortality modeling
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| Tag | 1 | 2 | Value |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20240013639 | ||
| 003 | MAP | ||
| 005 | 20240830135110.0 | ||
| 008 | 240830e20240415che|||p |0|||b|eng d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a6 | ||
| 100 | 1 | $0MAPA20240021146$aKrawiec, Michal | |
| 245 | 1 | 0 | $aMultivariate Lévy-type drift change detection and mortality modeling$cMichal Krawiec and Zbigniew Palmowski |
| 520 | $aIn 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 | ||
| 650 | 4 | $0MAPA20080555306$aMortalidad | |
| 650 | 4 | $0MAPA20080602437$aMatemática del seguro | |
| 650 | 4 | $0MAPA20080563448$aModelización | |
| 650 | 4 | $0MAPA20080545338$aSeguros | |
| 700 | 1 | $0MAPA20210032660$aPalmowski, Zbigniew | |
| 773 | 0 | $wMAP20220007085$g15/04/2024 Volúmen 14 - Número 1 - abril 2024 , p. 175-203$tEuropean Actuarial Journal$dCham, Switzerland : Springer Nature Switzerland AG, 2021-2022 | |
| 856 | $uhttps://link.springer.com/article/10.1007/s13385-023-00350-8 |