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

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

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Journal Paper

Paper Information

Journal: Iranian Journal of Fuzzy Systems Year:2023 | Volume:20 | Issue:3 Page(s): 159-175

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Title

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

Author(s)

Esfahani M. | Amini M. | Mohtashami Borzadaran G.R. | Dolati A. | Issue Writer Certificate

Keywords

Copula function

bivariate Gompertz--Makeham distribution

dependence measures

dependence structure

reliability

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.

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