Statistical estimation of the prediction uncertainty of physical models is typically hindered by the inadequacy of these models due to various approximations they are built upon. The prediction errors caused by model inadequacy can be handled either by correcting the model’s results or by adapting the model’s parameter uncertainty to generate prediction uncertainties representative, in a way to be defined, of model inadequacy errors. The main advantage of the latter approach (thereafter called PUI, for Parameter Uncertainty Inflation) is its transferability to the prediction of other quantities of interest based on the same parameters. A critical review of implementations of PUI in several areas of computational chemistry shows that it is biased, in the sense that it does not produce prediction uncertainty bands conforming to model inadequacy errors.

中文翻译：

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参数不确定性通胀谬误

物理模型的预测不确定性的统计估计通常由于这些模型基于各种近似而受到不足的阻碍。由模型不足引起的预测误差可以通过更正模型结果或通过调整模型的参数不确定性来生成以模型方式定义的代表不确定性的预测不确定性来处理。后一种方法的主要优点（此后称为PUI，用于参数不确定性通货膨胀）是基于相同参数的可移植性，可预测其他感兴趣的数量。对PUI在计算化学几个领域中的实施情况进行的严格审查显示，它存在偏见，