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Bayesian credibility for GLMs


Bayesian credibility for GLMs

Garrido, José ORCID: https://orcid.org/0000-0002-2016-7524 and Xacur, Oscar Alberto Quijano (2018) Bayesian credibility for GLMs. Insurance: Mathematics and Economics . ISSN 01676687 (In Press)

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Official URL: http://dx.doi.org/10.1016/j.insmatheco.2018.05.001


We revisit the classical credibility results of Jewell (1974) and Bühlmann (1967) to obtain credibility premiums for a GLM using a modern Bayesian approach. Here the prior distribution can be chosen without restrictions to be conjugate to the response distribution. It can even come from out–of–sample information if the actuary prefers.
Then we use the relative entropy between the “true” and the estimated models as a loss function, without restricting credibility premiums to be linear. A numerical illustration on real data shows the feasibility of the approach, now that computing power is cheap, and simulations software readily available.

Divisions:Concordia University > Faculty of Arts and Science > Mathematics and Statistics
Item Type:Article
Authors:Garrido, José and Xacur, Oscar Alberto Quijano
Journal or Publication:Insurance: Mathematics and Economics
  • Natural Sciences and Engineering Research Council of Canada (NSERC)
Digital Object Identifier (DOI):10.1016/j.insmatheco.2018.05.001
ID Code:984212
Deposited By: ALINE SOREL
Deposited On:27 Aug 2018 16:36
Last Modified:17 May 2020 00:00


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