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

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 reliabilit...

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Bibliographic Details
Published in:Iranian journal of fuzzy systems (Online) 2023-05, Vol.20 (3), p.159
Main Authors: Esfahani, M, Amini, M, Mohtashami-Borzadaran, G R, Dolati, A
Format: Article
Language:English
Subjects:
COVID-19
Fuzzy logic
Mortality
Random variables
Online Access:Get full text
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Summary: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.
ISSN:1735-0654
2676-4334
DOI:10.22111/ijfs.2023.7645