Enami Shohreh, Alamri Osama Abdulaziz
Department of Statistics, Payame Noor University, Tehran, Iran.
Department of Statistics, University of Tabuk, Tabuk, Saudi Arabia.
PLoS One. 2025 Jun 3;20(6):e0322996. doi: 10.1371/journal.pone.0322996. eCollection 2025.
The problem of monitoring statistical processes using complete data has been extensively studied by researchers. However, in fields such as reliability engineering and lifetime experiments, complete samples are often not available. To address this gap, we introduce four control charts designed for monitoring both parameters of a family of distributions known as the lower truncated proportional hazard rate model, specifically under progressively Type-II censoring. Three of these control charts are exponentially weighted moving average (EWMA) charts that utilize the likelihood ratio statistic and maximum likelihood estimators. The fourth chart is based on a novel weighted log-likelihood ratio statistic. We conduct a Monte Carlo simulation study to assess the performance of the proposed control charts. Finally, we present a practical example to illustrate the application of our methods.
研究人员对使用完整数据监测统计过程的问题进行了广泛研究。然而，在可靠性工程和寿命试验等领域，完整样本往往难以获得。为了弥补这一差距，我们引入了四个控制图，用于监测一类称为下截断比例风险率模型的分布参数，具体是在逐步II型截尾情况下。其中三个控制图是指数加权移动平均（EWMA）图，它们利用似然比统计量和最大似然估计量。第四个图基于一种新颖的加权对数似然比统计量。我们进行了蒙特卡罗模拟研究，以评估所提出控制图的性能。最后，我们给出一个实际例子来说明我们方法的应用。
