In this paper, we develop a version of the weighted Marshall-Olkin bivariate exponential model by incorporating a new parameter. This parameter describes the dependence structure between margins via a copula function. We choose the inference for margins method to estimate the model parameters along with the copula parameter, as this method offers more advantages than the maximum likelihood estimation method. Additionally, we conduct a comprehensive simulation study to investigate the behavior of the copula parameter estimator and the remaining parameters. Finally, an analysis of a real dataset on automobile insurance reveals that the Clayton copula characterizes the dependence structure within the Archimedean copula family
Makhdoom, I., & Sakhaei, A. (2023). On dependence of the weighted Marshall-Olkin bivariate exponential model in the presence of the copula function. Journal of Statistical Modelling: Theory and Applications, 4(1), 157-172. doi: 10.22034/jsmta.2024.21105.1125
MLA
Iman Makhdoom; Ali Sakhaei. "On dependence of the weighted Marshall-Olkin bivariate exponential model in the presence of the copula function", Journal of Statistical Modelling: Theory and Applications, 4, 1, 2023, 157-172. doi: 10.22034/jsmta.2024.21105.1125
HARVARD
Makhdoom, I., Sakhaei, A. (2023). 'On dependence of the weighted Marshall-Olkin bivariate exponential model in the presence of the copula function', Journal of Statistical Modelling: Theory and Applications, 4(1), pp. 157-172. doi: 10.22034/jsmta.2024.21105.1125
VANCOUVER
Makhdoom, I., Sakhaei, A. On dependence of the weighted Marshall-Olkin bivariate exponential model in the presence of the copula function. Journal of Statistical Modelling: Theory and Applications, 2023; 4(1): 157-172. doi: 10.22034/jsmta.2024.21105.1125
)