A Copula-Based Bivariate Composite Model for Modelling Claim Costs

被引:1
|
作者
Aradhye, Girish [1 ]
Tzougas, George [2 ]
Bhati, Deepesh [1 ]
Piccoli, Luca
机构
[1] Cent Univ Rajasthan, Dept Stat, Ajmer 305817, India
[2] Heriot Watt Univ, Maxwell Inst Math Sci, Dept Actuarial Math & Stat, Edinburgh EH14 4AS, Scotland
关键词
copulas; dependence parameter; Gumbel copula; Inverse Weibull distribution; Inverse Burr distribution; Paralogistic distribution; Weibull distribution;
D O I
10.3390/math12020350
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper aims to develop a new family of bivariate distributions for modelling different types of claims and their associated costs jointly in a flexible manner. The proposed bivariate distributions can be viewed as a continuous copula distribution paired with two marginals based on composite distributions. For expository purposes, the details of one of the proposed bivarite composite distributions is provided. The dependence measures for the resulting bivariate copula-based composite distribution are studied, and its fitting is compared with other bivariate composite distributions and existing bivariate distributions. The parameters of the proposed bivariate composite model are estimated via the inference functions for margins (IFM) method. The suitability of the proposed bivariate distribution is examined using two real-world insurance datasets, namely the motor third-party liability (MTPL) insurance dataset and Danish fire insurance dataset.
引用
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页数:17
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