Abstract

We propose a repetitive inspection plan that is based on the run-length of positive and negative test results. In a numerical analysis, we show that the new inspection plan outperforms previous ones in terms of the expected total cost as well as the average outgoing quality. The model parameters are often assumed to be known in advance, but we propose the use of a Bayesian method to estimate the point and interval estimates of the unknown parameters. We show that computational difficulties with prior distributions of the three parameters can be easily overcome with an appropriate MCMC method.

中文翻译：

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基于测试结果运行时间的重复检查方案：马尔可夫链蒙特卡洛方法

摘要

我们提出了一个基于阳性和阴性测试结果的重复检查计划。在数值分析中，我们表明，新的检查计划在预期总成本以及平均出库质量方面都优于以前的检查计划。通常假定模型参数事先已知，但是我们建议使用贝叶斯方法来估计未知参数的点和区间估计。我们表明，使用适当的MCMC方法可以轻松克服三个参数的先验分布带来的计算困难。