ABSTRACT Recently Mondal and Kundu [Mondal S, Kundu D. A new two sample type-II progressive censoring scheme. Commun Stat Theory Methods. 2018. doi:10.1080/03610926.2018.1472781] introduced a Type-II progressive censoring scheme for two populations. In this article, we extend the above scheme for more than two populations. The aim of this paper is to study the statistical inference under the multi-sample Type-II progressive censoring scheme, when the underlying distributions are exponential. We derive the maximum likelihood estimators (MLEs) of the unknown parameters when they exist and find out their exact distributions. The stochastic monotonicity of the MLEs has been established and this property can be used to construct exact confidence intervals of the parameters via pivoting the cumulative distribution functions of the MLEs. The distributional properties of the ordered failure times are also obtained. The Bayesian analysis of the unknown model parameters has been provided. The performances of the different methods have been examined by extensive Monte Carlo simulations. We analyse two data sets for illustrative purposes.

中文翻译：

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联合类型 II 渐进审查方案下对多个指数总体的精确推断

摘要 最近 Mondal 和 Kundu [Mondal S, Kundu D. 一种新的两个样本 II 型渐进审查方案。公共统计理论方法。2018. doi:10.1080/03610926.2018.1472781] 为两个人群引入了 II 型渐进式审查方案。在本文中，我们将上述方案扩展到两个以上的人群。本文的目的是研究多样本 II 类渐进式审查方案下的统计推断，当基础分布是指数分布时。我们推导出未知参数存在时的最大似然估计量 (MLE) 并找出它们的确切分布。已经建立了 MLE 的随机单调性，并且该属性可用于通过旋转 MLE 的累积分布函数来构建参数的精确置信区间。还获得了有序失效时间的分布特性。提供了未知模型参数的贝叶斯分析。不同方法的性能已经通过广泛的蒙特卡罗模拟进行了检查。出于说明目的，我们分析了两个数据集。