Article (Scientific journals)
Smoothed nonparametric maximum likelihood estimation of the risk distribution underlying bonus-malus systems
Denuit, Michel; Lambert, Philippe
2001In Proceedings of the Casualty Actuarial Society, LXXXVIII, p. 142-174
Peer reviewed
 

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Abstract :
[en] Mixed Poisson distributions are widely used for modeling claim counts when the portfolio is thought to be heterogeneous. The risk (or mixing) distribution then represents a measure of this heterogeneity. The aim of this paper is to use a variant of the Patilea and Rolin [15] smoothed version of the Simar [20] Non-Parametric Maximum Likelihood Estimator of the risk distribution in the mixed Poisson model. Empirical results based on two data sets from automobile third-party liability insurance demonstrate the relevance of this approach. The design of merit-rating schemes is discussed in the second part of the paper.
Disciplines :
Mathematics
Author, co-author :
Denuit, Michel
Lambert, Philippe  ;  Université de Liège - ULiège > Institut des sciences humaines et sociales > Méthodes quantitatives en sciences sociales
Language :
English
Title :
Smoothed nonparametric maximum likelihood estimation of the risk distribution underlying bonus-malus systems
Publication date :
2001
Journal title :
Proceedings of the Casualty Actuarial Society
Volume :
LXXXVIII
Pages :
142-174
Peer reviewed :
Peer reviewed
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