Non-informative priors in GUM Supplement 1

dc.creatorLira, Ignacio
dc.creatorGrientschnig, Dieter
dc.date.accessioned2024-01-10T12:07:00Z
dc.date.accessioned2024-05-02T17:49:20Z
dc.date.available2024-01-10T12:07:00Z
dc.date.available2024-05-02T17:49:20Z
dc.date.created2024-01-10T12:07:00Z
dc.date.issued2011
dc.identifier10.1016/j.measurement.2011.05.020
dc.identifier0263-2241
dc.identifierhttps://doi.org/10.1016/j.measurement.2011.05.020
dc.identifierhttps://repositorio.uc.cl/handle/11534/76232
dc.identifierWOS:000295194900035
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9269090
dc.description.abstractSupplement 1 to the 'Guide to the Expression of Uncertainty in Measurement' (GUM S1) proposes a Monte Carlo method for the propagation of the probability density functions (PDFs) assigned to the input quantities that are related to an output quantity through a measurement model. Guidance is provided in GUM Si for assigning PDFs to the input quantities for which data but no prior knowledge are available. The procedure relies on Bayes' theorem and on the use of appropriate non-informative priors. An inconsistency in the choice of such priors is pointed out. (C) 2011 Elsevier Ltd. All rights reserved.
dc.languageen
dc.publisherELSEVIER SCI LTD
dc.rightsacceso restringido
dc.subjectGUM Supplement 1
dc.subjectNon-informative priors
dc.subjectPoisson distribution
dc.titleNon-informative priors in GUM Supplement 1
dc.typeartículo


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