Título: Bayesian Structured Additive Models: An application to car insurance data
Palestrante: Giovani L. Silva (Universidade de Lisboa)
Local: Transmissão Online
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Resumo: This work was motivated by a car insurance study, comprising policies registered in Portugal mainland from 2011 to 2013, and involving some particularities, namely missing values and excess of zeros in the data set. It aims to analyse how claim frequency is influenced by policy risk factors in a car insurance application. Hence, risk profiles can be defined in order to apply adequate insurance premiums for policyholders and reduce monetary losses in insurance companies. The methodology is based on Structured Additive Models by using Bayesian approach via Markov chain Monte Carlo methods. Model selection suggested better fitting for zero-inflated negative binomial models, which were used for estimation of actuarial quantities of interest. Joint work with João Góis.