Mohtashami-Borzadaran V, Amini M, Ahmadi J
Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran.
J Appl Stat. 2021 Dec 2;50(4):984-1016. doi: 10.1080/02664763.2021.2006613. eCollection 2023.
In this paper, a new dependent model is introduced. The model is motivated using the structure of series-parallel systems consisting of two series-parallel systems with a random number of parallel sub-systems that have fixed components connected in series. The dependence properties of the proposed model are studied. Two estimation methods, namely the moment method, and the maximum likelihood method are applied to estimate the parameters of the distributions of the components based on observing the system's lifetime data. A Monte Carlo simulation study is used to evaluate the performance of the estimators. Two real data sets are used to illustrate the proposed method. The results are useful for researchers and practitioners interested in analyzing bivariate data related to extreme events.
本文介绍了一种新的相依模型。该模型是通过由两个串并联系统组成的串并联系统结构来构建的，其中并联子系统的数量是随机的，且子系统中的固定组件是串联连接的。研究了所提出模型的相依性质。基于观测到的系统寿命数据，应用两种估计方法，即矩估计法和最大似然估计法来估计组件分布的参数。使用蒙特卡罗模拟研究来评估估计量的性能。使用两个真实数据集来说明所提出的方法。研究结果对有兴趣分析与极端事件相关的双变量数据的研究人员和从业者有用。
