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Title: Modelling Unobserved Heterogeneity in Claim Counts Using Finite Mixture Models
Author: Bermúdez, Lluís
Karlis, Dimitris
Morillo, Isabel
Keywords: Anàlisi de regressió
Variables (Matemàtica)
Assegurances d'automòbils
Regression analysis
Variables (Mathematics)
Automobile insurance
Issue Date: Jan-2020
Publisher: MDPI
Abstract: When modelling insurance claim count data, the actuary often observes overdispersion and an excess of zeros that may be caused by unobserved heterogeneity. A common approach to accounting for overdispersion is to consider models with some overdispersed distribution as opposed to Poisson models. Zero-inflated, hurdle and compound frequency models are typically applied to insurance data to account for such a feature of the data. However, a natural way to deal with unobserved heterogeneity is to consider mixtures of a simpler models. In this paper, we consider k-finite mixtures of some typical regression models. (...)
Note: Reproducció del document publicat a:
It is part of: Risks , 2020, vol. 8, num. 1(10), p. 01-13
Related resource:
ISSN: 2227-9091
Appears in Collections:Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)

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