A Copula-Based Bivariate Composite Model for Modelling Claim Costs

Girish Aradhye, George Tzougas, Deepesh Bhati

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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.
Original languageEnglish
Article number350
Issue number2
Publication statusPublished - 22 Jan 2024


  • Gumbel copula
  • Inverse Burr distribution
  • Inverse Weibull distribution
  • Paralogistic distribution
  • Weibull distribution
  • copulas
  • dependence parameter

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Engineering (miscellaneous)
  • General Mathematics


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