Reliability Inference for a Copula-Based Series System Life Test Under Multiple Type-I Censoring

In this paper, we consider a multiple Type-I censored life test of series systems in which each component's lifetime belongs to the log-location-scale family of distributions with dependence. The dependence among lifetimes of components is generated by the Clayton copula with unknown copula parameter. We obtain the maximum likelihood estimates of the underlying parameters via EM algorithm under masked data and derive the Fisher information via missing information principle. The effect due to misspecification by independent models is investigated through the percentiles estimation of both the system's and components' failure time distributions by simulation study as well as a real data example.