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微小偏倚及其不确定性对不确定区间覆盖概率的影响 第1部分. 针对真实偏倚给定值的评估

Effect of insignificant bias and its uncertainty on the coverage probability of uncertainty intervals Part 1. Evaluation for a given value of the true bias.

作者信息

Synek Václav

机构信息

Faculty of the Environment, Jan Evangelista Purkyne University, Králova výsina 7, CZ-40096 Ustí nad Labem, Czech Republic.

出版信息

Talanta. 2006 Dec 15;70(5):1024-34. doi: 10.1016/j.talanta.2006.02.018. Epub 2006 Mar 29.

Abstract

This paper investigates the coverage probability of the uncertainty intervals determined in compliance with the GUM and EURACHEM Guide, which are defined by expanded uncertainty U about the results uncorrected with the insignificant biases and corrected with the significant biases. This coverage probability can significantly fall below the chosen level of confidence in some cases as Maroto et al. discovered by using the Monte Carlo method. Their numerical results obtained provided that only the beta errors have occurred in the test significance and findings that the coverage reduction depends on the mutual proportions of the magnitudes of the systematic error, overall uncertainty and bias uncertainty are confirmed in this paper by using probability calculus and numerical integration. This problem is also studied when all possible experimental biases, both significant and insignificant, are considered. From this point of view, the reduction of the coverage probability turns out to be less severe than from the previous one. The coverage probability is also investigated for some uncertainty intervals computed in different ways than the above mentioned documents recommend. The intervals defined by U about the results corrected with both significant and insignificant bias give always the same coverage probability equalling the chosen level of confidence. The intervals with some uncertainties modified or enlarged with the insignificant biases remove or moderate the coverage reduction.

摘要

本文研究了按照GUM和EURACHEM指南确定的不确定区间的覆盖概率,这些区间由扩展不确定度U定义,适用于未校正微小偏差但已校正显著偏差的结果。正如Maroto等人通过蒙特卡罗方法所发现的,在某些情况下,这种覆盖概率可能会显著低于选定的置信水平。他们获得的数值结果表明,在测试显著性中仅出现了贝塔误差,并且本文通过概率计算和数值积分证实了覆盖概率的降低取决于系统误差、总不确定度和偏差不确定度大小的相互比例。当考虑所有可能的实验偏差(包括显著偏差和微小偏差)时,也对该问题进行了研究。从这个角度来看,覆盖概率的降低结果比前一种情况要轻。还对以不同于上述文件推荐的方式计算的一些不确定区间的覆盖概率进行了研究。由U定义的、适用于已校正显著偏差和微小偏差的结果的区间,其覆盖概率始终相同,等于选定的置信水平。通过微小偏差修改或扩大某些不确定度的区间消除或减轻了覆盖概率的降低。

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