Abstract
Two robust methods of assessing the value and the uncertainty of the measurand from the samples of small number of experimental data are presented. Those methods should be used when some measurements results contain outliers, i.e. when the values of certain measurement significantly differ from the others. They allow to set a credible statistical parameters of the measurements with the use of all experimental data. The following considerations are illustrated by the numerical example of the interlaboratory measurement data key comparison. Compared are the results obtained by a classical method with rejection of outliers with two robust methods: a rescaled median absolute deviation MADS and an iterative two-criteria method.
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Volodarski, E., Warsza, Z.: Applications of the robust statistic estimation on the example of inter-laboratory measurements, pp. 260–267 (2013) (in Polish)
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© 2015 Springer International Publishing Switzerland
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Volodarsky, E.T., Warsza, Z.L. (2015). Examples of Robust Estimation with Small Number of Measurements. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Progress in Automation, Robotics and Measuring Techniques. Advances in Intelligent Systems and Computing, vol 352. Springer, Cham. https://doi.org/10.1007/978-3-319-15835-8_31
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DOI: https://doi.org/10.1007/978-3-319-15835-8_31
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-15834-1
Online ISBN: 978-3-319-15835-8
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