PHASE-TYPE DISTRIBUTIONS FOR CLAIM SEVERITY REGRESSION MODELING
@article{Bladt2021PHASETYPEDF, title={PHASE-TYPE DISTRIBUTIONS FOR CLAIM SEVERITY REGRESSION MODELING}, author={Martin Bladt}, journal={ASTIN Bulletin}, year={2021}, volume={52}, pages={417 - 448} }
Abstract This 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…
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References
SHOWING 1-10 OF 42 REFERENCES
A New Class of Severity Regression Models with an Application to IBNR Prediction
- Computer Science
- 2020
The proposed TG-LRMoE model is applied to fit the severity and reporting delay components of a European automobile insurance dataset and is shown to be useful and crucial for adequate prediction of incurred but not reported (IBNR) reserves through out-of-sample testing.
Mortality modeling and regression with matrix distributions
- MathematicsInsurance: Mathematics and Economics
- 2022
Inhomogeneous Markov Survival Regression Models
- Mathematics
- 2020
We propose new regression models in survival analysis based on homogeneous and inhomogeneous phase-type distributions. The intensity function in this setting plays the role of the hazard function.…
Matrix Mittag–Leffler distributions and modeling heavy-tailed risks
- MathematicsExtremes
- 2020
In this paper we define the class of matrix Mittag-Leffler distributions and study some of its properties. We show that it can be interpreted as a particular case of an inhomogeneous phase-type…
Fitting inhomogeneous phase‐type distributions to data: the univariate and the multivariate case
- MathematicsScandinavian Journal of Statistics
- 2020
The class of inhomogeneous phase‐type distributions (IPH) was recently introduced in Albrecher & Bladt (2019) as an extension of the classical phase‐type (PH) distributions. Like PH distributions,…
A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean
- MathematicsComput. Stat. Data Anal.
- 2009
Modeling and Evaluating Insurance Losses Via Mixtures of Erlang Distributions
- Engineering
- 2010
Abstract In this paper we suggest the use of mixtures of Erlang distributions with common scale parameter to model insurance losses. A modified expectation-maximization (EM) algorithm for parameter…
Fitting phase–type scale mixtures to heavy–tailed data and distributions
- Mathematics
- 2017
We consider the fitting of heavy tailed data and distributions with a special attention to distributions with a non–standard shape in the “body” of the distribution. To this end we consider a dense…