Estimation of the parameters of a Markov-modulated loss process in insurance

被引：11
|
作者：
Guillou, Armelle [1 ,2 ]
Loisel, Stephane [3 ]
Stupfler, Gilles [4 ]
机构：
[1] Univ Strasbourg, F-67084 Strasbourg, France
[2] CNRS, IRMA, UMR 7501, F-67084 Strasbourg, France
[3] Univ Lyon 1, Inst Sci Financiere & Assurances, F-69007 Lyon, France
[4] Aix Marseille Univ, CERGAM, EA 4225, F-13628 Aix En Provence 1, France
来源：
INSURANCE MATHEMATICS & ECONOMICS | 2013年 / 53卷 / 02期
关键词：
Markov-modulated Poisson process; Maximum likelihood estimator; Strong consistency; EM algorithm; PROBABILISTIC FUNCTIONS; POISSON PROCESSES; MODELS; CONSISTENT; ALGORITHM; CHAINS;
D O I：
10.1016/j.insmatheco.2013.07.003
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
We present a new model of loss processes in insurance. The process is a couple (N, L) where N is a univariate Markov-modulated Poisson process (MMPP) and L is a multivariate loss process whose behavior is driven by N. We prove the strong consistency of the maximum likelihood estimator of the parameters of this model and present an EM algorithm to compute it in practice. The method is illustrated with simulations and real sets of insurance data. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码：388 / 404
页数：17
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