Shen Pao-Sheng, Li Huai-Man
Department of Statistics, Tunghai University, Taichung, Taiwan.
J Appl Stat. 2024 Oct 14;52(5):1128-1143. doi: 10.1080/02664763.2024.2415412. eCollection 2025.
Field data provide important information on product reliability. Interval sampling is widely used for collection of field data, which typically report incident cases during a certain time period. Such sampling scheme induces doubly truncated (DT) data if the exact failure time is known. In many situations, the exact failure date is known only to fall within an interval, leading to doubly truncated and interval censored (DTIC) data. This article considers analysis of DTIC data under parametric failure time models. We consider a conditional likelihood approach and propose interval estimation for parameters and the cumulative distribution functions. Simulation studies show that the proposed method performs well for finite sample size.
现场数据提供了有关产品可靠性的重要信息。间隔抽样广泛用于现场数据的收集，现场数据通常报告特定时间段内的事件案例。如果确切的失效时间已知，这种抽样方案会产生双截尾（DT）数据。在许多情况下，确切的失效日期仅知道落在某个区间内，从而导致双截尾和区间删失（DTIC）数据。本文考虑在参数化失效时间模型下对DTIC数据进行分析。我们考虑一种条件似然方法，并提出参数和累积分布函数的区间估计。模拟研究表明，所提出的方法在有限样本量下表现良好。
