Bermúdez, LluísKarlis, Dimitris2017-02-032017-02-032012-120167-9473https://hdl.handle.net/2445/106474Bivariate Poisson regression models for ratemaking in car insurance have been previously used. They included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. These models are now revisited in order to consider alternatives. A 2-finite mixture of bivariate Poisson regression models is used to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, it is shown that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Finally, an EM algorithm is provided in order to ensure the models' ease-of-fit. These models are applied to an automobile insurance claims data set and it is shown that the modeling of the data set can be improved considerably.12 p.application/pdfeng(c) Elsevier B.V., 2012InflacióAnàlisi de regressióAssegurances d'accidentsVariables (Matemàtica)InflationRegression analysisAccident insuranceVariables (Mathematics)info:eu-repo/semantics/article6154072017-02-03info:eu-repo/semantics/openAccess