In this work, we consider the problem of estimating the parameters and predicting the unobserved or removed ordered data for the progressive type II censored flexible Weibull sample. Frequentist and Bayesian analyses are adopted for conducting the estimation and prediction problems. The likelihood method as well as the Bayesian sampling techniques is applied for the inference problems. The point predictors and credible intervals of unobserved data based on an informative set of data are computed. Markov Chain Monte Carlo samples are performed to compare the so-obtained methods, and one real data set is analyzed for illustrative purposes.

中文翻译：

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基于渐进式Ⅱ类删失数据的柔性威布尔分布估计与预测

在这项工作中，我们考虑了进行渐进式II型删失的灵活Weibull样本的参数估计和预测未观察到或除去的有序数据的问题。采用频繁和贝叶斯分析进行估计和预测问题。似然方法以及贝叶斯采样技术都适用于推理问题。计算基于信息丰富的数据集的预测点数和未观测数据的可信区间。进行马尔可夫链蒙特卡洛样本以比较所获得的方法，并出于说明目的分析了一个真实的数据集。