MATHMET

The European Centre for
Mathematics and Statistics in Metrology

Scientific journal papers

Scientific papers, guidelines, best-practice guides and relevant publications for mathematics and statistics in metrology are published by MATHMET members in various locations. In order to improve visibility of this work, MATHMET provides a searchable data base of relevant peer-reviewed scientific publications.

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Authors
Title
Journal
Year
F. Pennecchi, I. Kuselman, R. J. N. B. da Silva and D. Brynn HibbertRisk of a false decision on conformity of an environmental compartment due to measurement uncertainty of concentrations of two or more pollutantsChemosphere 202, 165-1762018
I. Kuselman, F. Pennecchi, R. J. N. B. da Silva, D. Brynn Hibbert and Elena AnchutinaTotal risk of a false decision on conformity of an alloy due to measurement uncertaintyTalanta 189, 666-6742018
V Cabral, L Ribeiro and J A SousaValidation of a high resistance calibration method based on a binary voltage dividerJ. of Physics: Conf. Series 1044 (2018) 012073 2018
L Martins, A Ribeiro, J Alves e Sousa, A Freire, S Fontul, F Batista and A MaiaUncertainty evaluation for the dynamic measurement of deflections with a falling-weight-type impulse load deviceJ. of Physics: Conf. Series 1044 (2018) 0120722018
Blaza Toman, Michael A. Nelson, Mary BednerRigorous evaluation of chemical measurement uncertainty: liquid chromatographic analysis methods using detector response factor calibrationMetrologia 54(3)2017
S. A. Bell, P. A. Carroll, S. L. Beardmore, C. England, N. ManderA methodology for study of in-service drift of meteorological humidity sensorsMetrologia 54(3)2017
A. Arduino, M. Chiampi, F. Pennecchi, L. Zilberti, O. BottauscioMonte Carlo Method for Uncertainty Propagation in Magnetic Resonance-based Electric Properties TomographyIEEE Transactions on Magnetics2017
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
S. Demeyer, N. Fischer, D. MarquisSurrogate model based sequential sampling estimation of conformance probability for computationally expensive systems: application to fire safety scienceJournal de la Société Française de Statistique, Vol. 158, No. 1, p.111-1382017
F. Rolle, F. Pennecchi, S. Perini, M. SegaMetrological traceability of Polycyclic Aromatic Hydrocarbons (PAHs) measurements in green tea and mateMeasurement 982017
I. Kuselman, F. Pennecchi, R. J. N. B. da Silva and D. Brynn HibbertConformity assessment of multicomponent materials or objects: Risk of false decisions due to measurement uncertaintyTalanta 164, 189-1952017
I. Kuselman, F. Pennecchi, R. J. N. B. da Silva and D. Brynn HibbertRisk of false decision on conformity of a multicomponent material when test results of the components' content are correlatedTalanta 174, 789-7962017
C. Elster and G. WübbelerBayesian regression versus application of least squares—an exampleMetrologia, 53(1), S102016
K. Klauenberg and C. ElsterMarkov chain Monte Carlo methods: an introductory exampleMetrologia, 53(1), S322016
O. Bodnar, C. Elster, J. Fischer, A. Possolo and B. TomanEvaluation of uncertainty in the adjustment of fundamental constantsMetrologia, 53(1), S462016
C. Elster and G. WübbelerBayesian inference using a noninformative prior for linear Gaussian random coefficient regression with inhomogeneous within-class variancesComput. Stat., 30(4)2016
A. B. ForbesA two-stage MCM/MCMC algorithm for uncertainty evaluationIn F. Pavese, M. Bär, J.-R. Filtz, A. B. Forbes, L. Pendrill and K. Shirono, editors, Advanced Mathematical and Computational Tools for Metrology IX, 159-170 2016
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