Reporting measurement uncertainty and coverage intervals near natural limits
Reporting measurement uncertainty and coverage intervals near natural limits
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DOI：
10.1039/b518084h
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发表时间：
2006-01-01
期刊：
影响因子：
4.2
通讯作者：
Ellison, Stephen L. R.
中科院分区：
文献类型：
--
作者：
Cowen, Simon;Ellison, Stephen L. R.
讨论了处理在可行范围内接近自然极限的数据的不同方法，如零或100%质量或摩尔分数，并就最合适的方法提出了建议。考虑的方法包括丢弃超出极限的观测值、将观测值移动到极限、基于学生t的经典可信区间的截断(如果在可行范围之外则将结果转移到极限)、假定正态分布的截断和重正规化、以及基于正态测量分布和可行范围内的一致先验的贝叶斯估计的最大密度区间。在考虑偏差和模拟评估覆盖范围的基础上，建议在大多数情况下，应首先根据学生t计算通常的可信区间，然后截断超出范围的部分以保留非对称区间，并在需要时将报告值调整到结果区间内，从而构建接近自然极限的可信区间。建议保留原标准不确定度，用于不确定度传播。
Different methods of treating data which lie close to a natural limit in a feasible range, such as zero or 100% mass or mole fraction, are discussed and recommendations made concerning the most appropriate. The methods considered include discarding observations beyond the limit, shifting observations to the limit, truncation of a classical confidence interval based on Student's t ( coupled with shifting the result to the limit if outside the feasible range), truncation and renormalisation of an assumed normal distribution, and the maximum density interval of a Bayesian estimate based on a normal measurement distribution and a uniform prior within the feasible range. Based on consideration of bias and simulation to assess coverage, it is recommended that for most purposes, a confidence interval near a natural limit should be constructed by first calculating the usual confidence interval based on Student's t, then truncating the out-of-range portion to leave an asymmetric interval and adjusting the reported value to within the resulting interval if required. It is suggested that the original standard uncertainty is retained for uncertainty propagation purposes.