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In this paper we describe the use of Bayesian inference for the evaluation of measurement uncertainty. The performance of the proposed approach is tested in a multivariate non linear measurement model in which the measurand is the ratio between two quantities: the first one being the sum of constant systematic effects and experimental indications, while the second one is referred to a measurement...
The maximum entropy approach is a flexible and powerful tool for assigning a probability distribution to a measurable quantity treated as a random variable, subjected to known moment constraints. The aim of this paper is to describe how the principle of maximum entropy may be used to transform information about the value of a quantity into a probability density function reflecting exactly that information...
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