报告题目：Semiparametric and Nonparametric Evaluation of First-Passage Distribution of Bivariate Degradation Processes
报告人：Ng, Hon Keung Tony
报告时间：2024年12月27日上午10:30-11:30
报告地点：X30456
报告摘要：In system engineering, the reliability of a system depends on the reliability of each subsystem (or component); those subsystems have their own performance characteristics, which can be dependent. The degradation of those dependent performance characteristics of the subsystems is used to assess the system’s reliability. Parametric frameworks have been developed to model bivariate and multivariate degradation processes in the literature; however, in practical situations, the underlying degradation process of a subsystem is usually unknown. In this work, we proposed different semiparametric and nonparametric methods to estimate the dependence on bivariate degradation data's first passage time distribution. The saddlepoint approximation and bootstrap methods are used to estimate the marginal FPT distributions empirically, and the empirical copula is used to estimate the joint distribution of two dependence degradation processes nonparametrically. A Monte Carlo simulation study and a numerical example are used to demonstrate the effectiveness and robustness of the proposed semiparametric and nonparametric approaches.
