In this article we consider the analysis of progressively censored competing risks data obtained from a simple step‐stress experiment. It is assumed that there are only two competing causes of failures at each stress level and the lifetime distribution of each one of them is one parameter exponential distribution. Based on the cumulative exposure model assumption, the conditional maximum likelihood estimators (MLEs) of the unknown parameters can be obtained in explicit forms. Confidence intervals of the unknown parameters based on the exact distributions of the conditional MLEs and percentile bootstrap method, are constructed. Further we obtain Bayes estimates and the associated credible intervals based on a very flexible Beta‐gamma prior on the unknown parameters. A simulation experiment has been performed to observe the performances of the different estimators.

中文翻译：

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在分步压力模型下分析存在竞争性风险数据时的渐进式II类审查

在本文中，我们考虑对从简单的逐步压力实验获得的渐进式审查竞争风险数据进行分析。假设在每个应力水平下只有两个相互竞争的失效原因，并且每个失效寿命的寿命分布都是一个参数指数分布。基于累积暴露模型假设，可以以显式形式获得未知参数的条件最大似然估计器（MLE）。基于条件MLE的精确分布和百分位数bootstrap方法，构造了未知参数的置信区间。此外，我们基于未知参数上非常灵活的Beta-γ值，获得了贝叶斯估计值和相关的可信区间。