This paper describes two prediction methods for predicting the non-observed (censored) units under progressive Type-II censored samples. The lifetimes under consideration are following a new two-parameter Pareto distribution. Furthermore, point and interval estimation of the unknown parameters of the new Pareto model is obtained. Maximum likelihood and Bayesian estimation methods are considered for that purpose. Since Bayes estimators cannot be expressed explicitly, Gibbs and the Markov Chain Monte Carlo techniques are utilized for Bayesian calculation. We use the posterior predictive density of the non-observed units to construct predictive intervals. A simulation study is performed to evaluate the performance of the estimators via mean square errors and biases and to obtain the best prediction method for the censored observation under progressive Type-II censoring scheme for different sample sizes and different censoring schemes.

中文翻译：

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新帕累托模型下渐进式II型截尾样本的最佳预测方法及应用

本文介绍了两种预测方法，用于预测渐进式 II 类删失样本下的非观察（删失）单元。所考虑的寿命遵循新的双参数帕累托分布。进一步得到了新帕累托模型未知参数的点估计和区间估计。为此目的考虑了最大似然和贝叶斯估计方法。由于无法明确表达贝叶斯估计量，因此使用 Gibbs 和马尔可夫链蒙特卡罗技术进行贝叶斯计算。我们使用非观测单元的后验预测密度来构建预测区间。