Carregant...
Fitxers
Tipus de document
ArticleVersió
Versió acceptadaData de publicació
Llicència de publicació
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/164643
Multivariate count data generalized linear models: Three approaches based on the Sarmanov distribution
Títol de la revista
Director/Tutor
ISSN de la revista
Títol del volum
Recurs relacionat
Resum
Starting from the question: What is the accident risk of an insured individual?, we consider that the customer has contracted policies in different insurance lines: motor and home. Three models based on the multivariate Sarmanov distribution are analyzed. Driven by a real data set that takes into account three types of accident risks, two for motor and one for home, three trivariate Sarmanov distributions with generalized linear models (GLMs) for marginals are considered and fitted to the data. To estimate the parameters of these three models, we discuss a method for approaching the maximum likelihood (ML) estimators. Finally, the three models are compared numerically with the simpler trivariate Negative Binomial GLM and with elliptical copula based models.
Citació
Citació
BOLANCÉ LOSILLA, Catalina, VERNIC, Raluca. Multivariate count data generalized linear models: Three approaches based on the Sarmanov distribution. _Insurance Mathematics and Economics_. 2019. Vol. 85, núm. 89-103. [consulta: 20 de gener de 2026]. ISSN: 0167-6687. [Disponible a: https://hdl.handle.net/2445/164643]