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• W2020135329 startingPage "S159" @default.
• W2020135329 abstract "The Guide to the Expression of Uncertainty in Measurement (GUM) has proven to be a major step towards the harmonization of uncertainty evaluation in metrology. Its procedures contain elements from both classical and Bayesian statistics. The recent supplements 1 and 2 to the GUM appear to move the guidelines towards the Bayesian point of view, and they produce a probability distribution that shall encode one's state of knowledge about the measurand. In contrast to a Bayesian uncertainty analysis, however, Bayes' theorem is not applied explicitly. Instead, a distribution is assigned for the input quantities which is then 'propagated' through a model that relates the input quantities to the measurand. The resulting distribution for the measurand may coincide with a distribution obtained by the application of Bayes' theorem, but this is not true in general." @default.
• W2020135329 created "2016-06-24" @default.
• W2020135329 creator A5084419307 @default.
• W2020135329 date "2014-07-11" @default.
• W2020135329 modified "2023-09-26" @default.
• W2020135329 title "Bayesian uncertainty analysis compared with the application of the GUM and its supplements" @default.
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• W2020135329 doi "https://doi.org/10.1088/0026-1394/51/4/s159" @default.
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