2026-04-18T03:46:30Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/1182792025-12-04T22:59:13Zcom_2072_1057col_2072_478911col_2072_478917

Multivariate count data generalized linear models: Three approaches based on the Sarmanov Distribution [WP] Bolancé Losilla, Catalina Vernic, Raluca Variables (Matemàtica) Variables aleatòries Teoria de distribucions (Anàlisi funcional) Teoria de l'estimació Variables (Mathematics) Random variables Theory of distributions (Functional analysis) Estimation theory Starting from the question: “What is the accident risk of an insured?”, this paper considers a multivariate approach by taking into account three types of accident risks and the possible dependence between them. Driven by a real data set, we propose three trivariate Sarmanov distributions with generalized linear models (GLMs) for marginals and incorporate various individual characteristics of the policyholders by means of explanatory variables. Since the data set was collected over a longer time period (10 years), we also added each individual’s exposure to risk. To estimate the parameters of the three Sarmanov distributions, we analyze a pseudo-maximumlikelihood method. Finally, the three models are compared numerically with the simpler trivariate Negative Binomial GLM. 2017-11-29T15:47:23Z 2017-11-29T15:47:23Z 2017 2017-11-29T15:47:23Z info:eu-repo/semantics/workingPaper Reproducció del document publicat a: http://www.ub.edu/irea/working_papers/2017/201718.pdf IREA – Working Papers, 2017, IR17/18 [WP E-IR17/18] cc-by-nc-nd, (c) Bolancé Losilla et al., 2017 http://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Universitat de Barcelona. Facultat d'Economia i Empresa Documents de treball (Institut de Recerca en Economia Aplicada Regional i Pública (IREA))