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Inference for a simple step-stress model based on ordered ranked set sampling

机译:基于有序排序集采样的简单阶跃应力模型的推论

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In this paper, we considered the inference problem on simple step-stress accelerated life test data from one-parameter exponential distribution under type-I censored ordered ranked set sample with cumulative exposure model. The Bayesian estimators and credible intervals for the model parameters are developed and compared with the corresponding estimators based on simple random sampling. Two real data sets and numerical simulation evaluations are presented to illustrate all the results developed here. The simulation study indicated that the proposed Bayes estimators and credible intervals based on ordered ranked set sampling performed better than their counterparts using simple random sampling. (C) 2019 Published by Elsevier Inc.
机译:在本文中,我们考虑了在具有累积暴露模型的I型删失有序排序集样本下,从单参数指数分布的简单阶跃应力加速寿命测试数据推断问题。开发了贝叶斯估计量和模型参数的可信区间,并将其与基于简单随机抽样的相应估计量进行比较。给出了两个实际数据集和数值模拟评估,以说明此处开发的所有结果。仿真研究表明,基于有序排序集抽样的贝叶斯估计器和可信区间的性能优于使用简单随机抽样的贝叶斯估计器和可信区间。 (C)2019由Elsevier Inc.发布

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