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使用帕累托模型的II型统一渐进混合删失样本的经典和贝叶斯推断

Classical and Bayesian Inference Using Type-II Unified Progressive Hybrid Censored Samples for Pareto Model.

作者信息

Nagy M, Alrasheedi Adel Fahad

机构信息

Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia.

出版信息

Appl Bionics Biomech. 2022 Apr 29;2022:2073067. doi: 10.1155/2022/2073067. eCollection 2022.

Abstract

In the lifetime and reliability experiments, the censored samples play a fundamental and important role in order to control time and cost. The researchers developed the censored sample schemes to solve the problems that arise by applying the previous methods. Recently, Górny and Cramer (2018) proposed a new general type of censored sample called Type-II unified progressive hybrid censored sample. In this paper, we present an overview of the Type-II unified progressive hybrid censored sample. We used this censored sample to compute the maximum likelihood estimates of unknown parameters from the Pareto distribution, as well as Bayesian estimates for unknown parameters under three different error loss functions. The point and interval Bayesian predictions one- and two-sample Bayesian predictions from the Pareto distribution are shown. Simulation studies are carried out to compare the efficacy of the various inference approaches. Finally, real data sets are examined to determine the applicability of the proposed model and various estimating approaches.

摘要

在寿命和可靠性实验中,删失样本对于控制时间和成本起着至关重要的作用。研究人员开发了删失样本方案来解决应用先前方法时出现的问题。最近,戈尔尼和克莱默(2018年)提出了一种新的通用类型的删失样本,称为II型统一渐进混合删失样本。在本文中,我们对II型统一渐进混合删失样本进行了概述。我们使用这种删失样本计算帕累托分布中未知参数的最大似然估计,以及在三种不同误差损失函数下未知参数的贝叶斯估计。展示了来自帕累托分布的点估计和区间贝叶斯预测、单样本和两样本贝叶斯预测。进行了模拟研究以比较各种推断方法的有效性。最后,检查实际数据集以确定所提出模型和各种估计方法的适用性。

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