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

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. [ FROM AUTHOR] Copyright of Iranian Journal of Fuzzy Systems is the property of University of Sistan & Baluchestan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)