Implementation of the calibration's VIM3 definition using the matrix of variance-covariance of input data

Verfasser / Beitragende:
[Marc Priel, Michèle Désenfant]
Ort, Verlag, Jahr:
2015
Enthalten in:
Accreditation and Quality Assurance, 20/2(2015-04-01), 107-114
Format:
Artikel (online)
ID: 605466246
LEADER caa a22 4500
001 605466246
003 CHVBK
005 20210128100306.0
007 cr unu---uuuuu
008 210128e20150401xx s 000 0 eng
024 7 0 |a 10.1007/s00769-015-1107-6  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00769-015-1107-6 
245 0 0 |a Implementation of the calibration's VIM3 definition using the matrix of variance-covariance of input data  |h [Elektronische Daten]  |c [Marc Priel, Michèle Désenfant] 
520 3 |a This paper discusses the effects following the implementation of the concept of calibration presented in the 3rd edition of the international vocabulary of metrology—basic and general concepts and associated terms (VIM) and the repercussions of practitioners adopting VIM3. The new definition leads to modifications in the treatment of calibration data. It is now necessary to establish a relation which allows obtaining any measurement result from any indication of the measuring instrument. This relation takes into account uncertainties and any covariances, both on the values of the standards used and on the indications and maybe even the covariances. The usual statistical technique of regression, the ordinary least squares adjustment, does not generally enable to reach this goal. As a result, more sophisticated methods need to be used, for instance the Generalised Gauss Markov Regression. We compared both methods on a gas chromatograph calibration example. 
540 |a Springer-Verlag Berlin Heidelberg, 2015 
690 7 |a Calibration  |2 nationallicence 
690 7 |a Metrological terminology  |2 nationallicence 
690 7 |a VIM  |2 nationallicence 
690 7 |a Ordinary least squares (OLS)  |2 nationallicence 
690 7 |a Generalised Gauss Markov Regression (GGMR)  |2 nationallicence 
690 7 |a Measurement uncertainty  |2 nationallicence 
690 7 |a Variance-covariance matrix  |2 nationallicence 
700 1 |a Priel  |D Marc  |u Laboratoire national de métrologie et d'essais, 1 rue Gaston Boissier, 75724, Paris, France  |4 aut 
700 1 |a Désenfant  |D Michèle  |u Laboratoire national de métrologie et d'essais, 1 rue Gaston Boissier, 75724, Paris, France  |4 aut 
773 0 |t Accreditation and Quality Assurance  |d Springer Berlin Heidelberg  |g 20/2(2015-04-01), 107-114  |x 0949-1775  |q 20:2<107  |1 2015  |2 20  |o 769 
856 4 0 |u https://doi.org/10.1007/s00769-015-1107-6  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00769-015-1107-6  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Priel  |D Marc  |u Laboratoire national de métrologie et d'essais, 1 rue Gaston Boissier, 75724, Paris, France  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Désenfant  |D Michèle  |u Laboratoire national de métrologie et d'essais, 1 rue Gaston Boissier, 75724, Paris, France  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Accreditation and Quality Assurance  |d Springer Berlin Heidelberg  |g 20/2(2015-04-01), 107-114  |x 0949-1775  |q 20:2<107  |1 2015  |2 20  |o 769