شماره ركورد كنفرانس :
3254
عنوان مقاله :
Survival analysis of a new compounded bivariate failure time distribution and its generalization
Author/Authors :
ُُShirin ُُُShoaee Department of Statistics - Faculty of Mathematical Sciences, Shahid Beheshti University , Shabnam Shoaee Faculty of Computer and Information Technology Engineering - Qazvin Branch, Islamic Azad University, Qazvin
كليدواژه :
Shock model , EM algorithm , Competing risk model , Bivariate model
عنوان كنفرانس :
پنجمين كنفرلنس بين المللي قابليت اطمينان و ايمني
چكيده لاتين :
In this paper, we consider that two bivariate models based on the Gompertz distribution and the proposed methods of Marshall and Olkin (1967) in bivariate case and Marshall and Olkin (1997) in the univariate cases. In the second case, their method is generalized to bivariate case and a new bivariate distribution is introduced. These new bivariate distributions have natural interpretations, and they can be applied in fatal shock models or in competing risks models. We call these new distributions as the Marshall Olkin bivariate Gompertz (MOBGP) distribution and bivariate Gompertz-geometric (BGPG) distribution, respectively. Moreover, the MOBGP can be obtained as a special case of the BGPG model. Then, the various properties of the new distributions are investigated. The BGPG distribution has five parameters and the maximum likelihood estimators cannot be obtained in closed form. We propose to use the EM algorithm, and it is observed that the implementation of the EM algorithm is quite straightforward. Also, one data analysis is provided for illustrative purposes