van der Veen, A M H; Cox, M G (2021) Getting started with uncertainty evaluation using the Monte Carlo method in R. Accreditation and Quality Assurance, 26 (3). pp. 129-141.

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Abstract

The evaluation of measurement uncertainty is often perceived by laboratory staff as complex and quite distant from daily practice. Nevertheless, standards such as ISO/IEC 17025, ISO 15189 and ISO 17034 that describe competence of laboratories require that measurement uncertainty is evaluated and as required reported. In response to this need, a European project entitled ``Advancing measurement uncertainty -- comprehensive examples for key international standards'' started in July 2018 that aims at developing examples that contribute to a better understanding of what is required and aid in implementing such evaluations in calibration, testing and research.

The principle applied in the project is ``learning by example''. Past experience with guidance documents such as EA~4/02 and the EuraChem/CITAC guide on measurement uncertainty has shown that for practitioners it is often easier to rework and adapt an existing example than to try to develop something from scratch. In this introductory paper, it is shown how the Monte Carlo method of GUM (Guide to the expression of Uncertainty in Measurement) Supplement~1 can be implemented in R , an environment for mathematical and statistical computing. It is also shown how the law of propagation of uncertainty can be implemented in the same environment, taking advantage of the possibility to evaluate the partial derivatives numerically, so that these do not need to be derived by analytic differentiation. The implementations are shown for the well-known mass calibration example from EA~4/02.

Item Type:	Article
Keywords:	Measurement uncertainty, Monte Carlo, R, calibration, testing
Subjects:	Mathematics and Scientific Computing > Measurement Uncertainties
Divisions:	Data Science
Identification number/DOI:	10.1007/s00769-021-01469-5
Last Modified:	28 Mar 2022 14:46
URI:	https://eprintspublications.npl.co.uk/id/eprint/9403