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Credibililty Theory for Generalized Linear and Mixed Models

Title:

Credibililty Theory for Generalized Linear and Mixed Models

Garrido, Jose and Zhou, Jun (2006) Credibililty Theory for Generalized Linear and Mixed Models. Technical Report. Concordia University. Department of Mathematics & Statistics, Montreal, Quebec.

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Abstract

Generalized linear models (GLMs) are gaining popularity as a statistical analysis method for insurance data. For segmented portfolios, as in car insurance, the question of credibility arises naturally; how many observations are needed in a risk class before the GLM estimators can be considered credible? In this paper we study the limited fluctuations credibility of the GLM estimators as well as in the extended case of generalized linear mixed model (GLMMs). We show how credibility depends on the sample size, the distribution of covariates and the link function. This provides a mechanism to obtain confidence intervals for the GLM and GLMM estimators.

Divisions:Concordia University > Faculty of Arts and Science > Mathematics and Statistics
Item Type:Monograph (Technical Report)
Authors:Garrido, Jose and Zhou, Jun
Series Name:Department of Mathematics & Statistics. Technical Report No. 5/06
Corporate Authors:Concordia University. Department of Mathematics & Statistics
Institution:Concordia University
Date:December 2006
Keywords:GLMs, GLMMs, limited fluctuations credibility, confidence intervals
ID Code:6676
Deposited By:DIANE MICHAUD
Deposited On:03 Jun 2010 16:49
Last Modified:08 Dec 2010 18:21
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