Shoaee, Shirin, Khorram, Esmaeil. (1398). A generalization of Marshall-Olkin bivariate Pareto model and its applications in shock and competing risk models. نشریه مهندسی عمران امیرکبیر, 1(1), 69-87. doi: 10.22060/ajmc.2018.14869.1012
Shirin Shoaee; Esmaeil Khorram. "A generalization of Marshall-Olkin bivariate Pareto model and its applications in shock and competing risk models". نشریه مهندسی عمران امیرکبیر, 1, 1, 1398, 69-87. doi: 10.22060/ajmc.2018.14869.1012
Shoaee, Shirin, Khorram, Esmaeil. (1398). 'A generalization of Marshall-Olkin bivariate Pareto model and its applications in shock and competing risk models', نشریه مهندسی عمران امیرکبیر, 1(1), pp. 69-87. doi: 10.22060/ajmc.2018.14869.1012
Shoaee, Shirin, Khorram, Esmaeil. A generalization of Marshall-Olkin bivariate Pareto model and its applications in shock and competing risk models. نشریه مهندسی عمران امیرکبیر, 1398; 1(1): 69-87. doi: 10.22060/ajmc.2018.14869.1012

A generalization of Marshall-Olkin bivariate Pareto model and its applications in shock and competing risk models

AUT Journal of Mathematics and Computing
مقاله 7، دوره 1، شماره 1، اردیبهشت 2020، صفحه 69-87    اصل مقاله (655.49 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22060/ajmc.2018.14869.1012
نویسندگان
Shirin Shoaee* 1؛ Esmaeil Khorram2
1Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
2Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
چکیده
Statistical inference for extremes has been a subject of intensive research during the last years. In this paper, we generalize the Marshall-Olkin bivariate Pareto distribution. In this case, a new bivariate distribution is introduced by compounding the Pareto Type $\rm{II}$ and geometric distributions. This new bivariate distribution has natural interpretations and can be applied in fatal shock models or in competing risks models. We call the new proposed model Marshall-Olkin bivariate Pareto-geometric (MOBPG) distribution, and then investigate various properties of the new distribution. This model has five unknown parameters and the maximum likelihood estimators cannot be afforded in explicit structure. We suggest to use the EM algorithm to calculate the maximum likelihood estimators of the unknown parameters, and this structure is quite flexible. Also, Monte Carlo simulations are performed to investigate the effectiveness of the proposed algorithm. Finally, we analyze a real data set to investigate our purposes.
کلیدواژه‌ها
Bivariate model؛ Competing risk model؛ Expectation-Maximization algorithm؛ Pareto Type $\rm{II}$ distribution؛ Shock model
مراجع
آمار
تعداد مشاهده مقاله: 50,976
تعداد دریافت فایل اصل مقاله: 1,135
پیوندهای مفید
آمار
تعداد نشریات9
تعداد شماره‌ها455
تعداد مقالات5,771
تعداد مشاهده مقاله8,375,224
تعداد دریافت فایل اصل مقاله6,933,601