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On the adjustment of inconsistent data using the Birge ratio

机译:关于使用Birge比调整不一致的数据

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摘要

The Birge ratio is applied in metrology to enlarge quoted uncertainties when combining inconsistent measurement results on the same measurand. We discuss the statistical model underlying such a procedure and argue that the resulting uncertainty associated with the adjusted value is underrated. We provide a simple modification of this uncertainty on the basis of an objective Bayesian inference. While the proposed uncertainty approaches that obtained by the conventional procedure for a large number n of combined measurement results, differences are significant for small n. For example, for n = 4 we get an increase of 73% in the standard uncertainty associated with the adjusted value, and for n = 10 the increase is still 13%. We derive the posterior distribution for the adjusted value in closed form, including a 95% credible interval. In addition, we show that our results do not only hold when the distribution of the measurement results is assumed to be Gaussian, but for a whole family of (elliptically contoured) location-scale distributions. We illustrate the modified Birge method by its application to data from the 2002 adjustment of the Newtonian constant of gravitation.
机译:当在相同的被测件上组合不一致的测量结果时,将伯奇比应用于度量学中以扩大引用的不确定性。我们讨论了此类程序的统计模型,并认为与调整后的值相关的不确定性被低估了。我们基于客观贝叶斯推断对这种不确定性进行简单修改。尽管所提出的不确定性方法接近了通过常规方法获得的n个组合测量结果的数量,但对于小n个而言,差异却很明显。例如,对于n = 4,与调整值相关的标准不确定度增加了73%,对于n = 10,仍然增加了13%。我们以封闭形式(包括95%可信区间)得出调整后值的后验分布。此外,我们表明,不仅在假设测量结果的分布为高斯分布时,而且对于整个(椭圆形轮廓)位置比例分布族,我们的结果都不成立。我们通过将其应用到2002年牛顿引力常数调整数据中来说明改进的Birge方法。

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