Klauenberg, K; Martens, S; Bosnjakovic, A; Cox, M G; van der Veen, A M H; Elster, C (2022) The GUM perspective on straight-line errors-in-variables regression. Measurement, 187. 110340

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Abstract

Following the Guide to the expression of uncertainty in measurement (GUM), the slope and intercept in straight-line regression tasks can be estimated and their uncertainty evaluated by defining a measurement model. Minimizing the weighted total least-squares functional appropriately defines such a model when both regression input quantities (

Item Type:	Article
Keywords:	Errors-in-variables; Straight-line regression; Weighted total least-squares; Law of propagation of uncertainty; Monte Carlo method; Implicit measurement model
Subjects:	Mathematics and Scientific Computing > Measurement Uncertainties
Divisions:	Data Science
Identification number/DOI:	10.1016/j.measurement.2021.110340
Last Modified:	21 Oct 2022 10:37
URI:	https://eprintspublications.npl.co.uk/id/eprint/9532