MATHMET

The European Centre for
Mathematics and Statistics in Metrology

Recent relevant journal papers

Authors
Title
Journal
Year
C. Elster, G. WübbelerBayesian inference using a noninformative prior for linear Gaussian random coefficient regression with inhomogeneous within-class variances.Comput. Stat., 32(1), 51--692017
S. Eichstädt, C. Elster, I.M. Smith, T.J. EswardEvaluation of dynamic measurement uncertainty – an open-source software package to bridge theory and practice.J. Sens. Sens. Syst., 6 97-1052017
S. Demeyer, N. FischerBayesian framework for proficiency tests using auxiliary information on laboratoriesAccreditation and Quality Assurance, February 2017, Volume 22, Issue 1, pp 1–192017
P. Ceria, S. Ducourtieux, Y. Boukellal, A. Allard, N. Fischer and N. FeltinModelling of the X,Y,Z positioning errors and uncertainty evaluation for the LNE's mAFM using the Monte Carlo methodMeasurement Science and Technology, Volume 28, Number 3 2017
N. Clouet-Foraison, F. Gaie-Levrel, L. Coquelin, G. Ebrard, P. Gillery, V. DelatourAbsolute Quantification of Bionanoparticles by Electrospray Differential Mobility Analysis: An Application to Lipoprotein Particle Concentration MeasurementsAnal. Chem., 2017, 89 (4), pp 2242–22492017

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The propagation of measurement uncertainty using the GUM Supplement 2 Monte Carlo method requires an efficient implementation in the case of dynamic measurements in order to achieve high accuracies.
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