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Bayesian inference for the pairwise probability of agreement using data from several measurement systems
Quality Engineering ( IF 2 ) Pub Date : 2021-06-11 , DOI: 10.1080/08982112.2021.1931317
Mário de Castro 1 , Manuel Galea 2
Affiliation  

Abstract

This article deals with Bayesian inference in the comparison of measurement systems. Agreement between two systems can be evaluated using data from several measurement systems and using only data from the two systems being compared. With a measurement error model for replicated observations and the probability of agreement to compare measurement systems, we develop methods to compare measurement systems with either homoscedastic or heteroscedastic measurement errors under the Bayesian paradigm via Markov chain Monte Carlo methods. A graphical tool is described to check model adequacy. The methodology developed in the article is illustrated using a real dataset and through simulations.



中文翻译:

使用来自多个测量系统的数据对成对一致性概率进行贝叶斯推理

摘要

本文讨论测量系统比较中的贝叶斯推理。可以使用来自多个测量系统的数据并仅使用来自被比较的两个系统的数据来评估两个系统之间的一致性。通过用于重复观测的测量误差模型和比较测量系统的一致性概率,我们开发了通过马尔可夫链蒙特卡罗方法在贝叶斯范式下比较测量系统与同方差或异方差测量误差的方法。描述了一个图形工具来检查模型的充分性。本文中开发的方法使用真实数据集并通过模拟进行了说明。

更新日期:2021-06-11
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