We review and contrast frequentist and Bayesian definitions of tolerance regions. We give conditions under which for large samples a Bayesian region also has frequentist validity, and study the latter for smaller samples in a simulation study. We discuss a computational strategy for computing a Bayesian two-sided tolerance interval for a Gaussian future variable, and apply this to the case of possibly unbalanced linear mixed models. We illustrate the method on a quality control experiment from the pharmaceutical industry.

翻译：我们审查并对比常客和巴耶斯人对容忍区域的定义。 我们给大型样本提供一种条件,让贝耶斯地区也具有常客有效性,并在模拟研究中研究后者的较小样本。 我们讨论计算巴伊斯人对高斯未来变数的双向容忍间隔的计算策略,并将这一策略应用于可能不平衡的线性混合模型。 我们展示了制药业质量控制实验的方法。