A new copula-based bivariate Gompertz--Makeham model and its application to COVID-19 mortality data

Esfahani, M.; Amini, M.; Mohtashami-Borzadaran, G. R.; Dolati, A.

doi:10.22111/ijfs.2023.7645

Document Type : Research Paper

Authors

¹ Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Iran

² Department of Statistics, Ordered ِData, Reliability and Dependency Center of Excellence, Ferdowsi University of Mashhad, P.O. Box 91775-1159, Mashhad, Iran

³ Department of Statistics, Faculty of Mathematical Sciences, Yazd University, Yazd, Iran

https://doi.org/10.22111/ijfs.2023.7645

Abstract

One of the useful distributions in modeling mortality (or failure) data is the univariate Gompertz--Makeham distribution. To examine the relationship between the two variables, the extended bivariate Gompertz--Makeham distribution is introduced, and its properties are provided. Also, some reliability indices, including aging intensity and stress-strength reliability, are calculated for the proposed model. Here, a new copula function is constructed based on the extended bivariate Gompertz--Makeham distribution. Some of its features including dependency properties, such as dependence structure, some measures of dependence, and tail dependence, are studied.
The estimation of the parameters of new copula is presented, and at the end, a simulation study and a performance analysis based on the real data are presented. So, by analyzing the mortality data due to COVID-19, the appropriateness of the proposed model is examined.

Keywords

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A new copula-based bivariate Gompertz--Makeham model and its application to COVID-19 mortality data

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Volume 20, Issue 3May and June 2023Pages 159-175

Volume 20, Issue 3
May and June 2023
Pages 159-175