Phase-type distributions for claim severity regression modeling
Objetos digitales
| Tag | 1 | 2 | Value |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20220014984 | ||
| 003 | MAP | ||
| 005 | 20220518131118.0 | ||
| 008 | 220518e20220509esp|||p |0|||b|spa d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a6 | ||
| 100 | 1 | $0MAPA20220005265$aBladt, Martin | |
| 245 | 1 | 0 | $aPhase-type distributions for claim severity regression modeling$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 | |
| 773 | 0 | $wMAP20077000420$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 |