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Phase-type distributions for claim severity regression modeling

Phase-type distributions for claim severity regression modeling
Recurso electrónico / Electronic resource
MARC record
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005  20220518131118.0
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040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
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1001 ‎$0‎MAPA20220005265‎$a‎Bladt, Martin
24510‎$a‎Phase-type distributions for claim severity regression modeling‎$c‎Martin Bladt
520  ‎$a‎This paper addresses the task of modeling severity losses using segmentation when the data distribution does not fall into the usual regression frameworks. This situation is not uncommon in lines of business such as third-party liability insurance, where heavy-tails and multimodality often hamper a direct statistical analysis. We propose to use regression models based on phase-type distributions, regressing on their underlying inhomogeneous Markov intensity and using an extension of the expectationmaximization algorithm. These models are interpretable and tractable in terms of multistate processes and generalize the proportional hazards specification when the dimension of the state space is larger than 1. We show that the combination of matrix parameters, inhomogeneity transforms, and covariate information provides flexible regression models that effectively capture the entire distribution of loss severities.
540  ‎$a‎La copia digital se distribuye bajo licencia "Attribution 4.0 International (CC BY 4.0)"‎$f‎‎$u‎https://creativecommons.org/licenses/by/4.0‎$9‎43
650 4‎$0‎MAPA20080579258‎$a‎Cálculo actuarial
650 4‎$0‎MAPA20080602437‎$a‎Matemática del seguro
650 4‎$0‎MAPA20080593063‎$a‎Regresión no lineal
7730 ‎$w‎MAP20077000420‎$g‎09/05/2022 Volumen 52 Número 2 - mayo 2022 , p. 417 - 448‎$x‎0515-0361‎$t‎Astin bulletin‎$d‎Belgium : ASTIN and AFIR Sections of the International Actuarial Association
856  ‎$q‎application/pdf‎$w‎1115368‎$y‎Recurso electrónico / Electronic resource