In this paper, a competing risks model is analyzed based on improved adaptive type-II progressive censored sample (IAT-II PCS). Two independent competing causes of failures are considered. It is assumed that lifetimes of the competing causes of failure follow exponential distributions with different means. Maximum likelihood estimators (MLEs) for the unknown model parameters are obtained. Using asymptotic normality property of MLE, the asymptotic confidence intervals are constructed. Existence and uniqueness properties of the MLEs are studied. Further, bootstrap confidence intervals are computed. The Bayes estimators are obtained under symmetric and asymmetric loss functions with non-informative and informative priors. For informative priors, independent gamma distributions are considered. Highest posterior density (HPD) credible intervals are obtained. A Monte Carlo simulation study is carried out to compare performance of the established estimates. Furthermore, three different optimality criteria are proposed to obtain the optimal censoring plan. Finally, a real-life data set is considered for illustrative purposes.

翻译：本文基于改进自适应II型渐进删失样本(IAT-II PCS)分析了竞争风险模型。考虑了两个独立的竞争失效原因，假设各竞争失效原因的寿命服从不同均值的指数分布。获得了未知模型参数的最大似然估计(MLEs)，并利用MLE的渐近正态性构建了渐近置信区间。研究了MLE的存在性与唯一性性质，进一步计算了Bootstrap置信区间。在非信息先验与信息先验下，基于对称和非对称损失函数获得了贝叶斯估计；信息先验采用独立伽马分布，并得到了最高后验密度(HPD)可信区间。通过蒙特卡罗模拟研究比较了所提估计量的性能，同时提出了三种最优准则以确定最优删失方案。最后，采用实际数据集进行了示例分析。