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Uncertainty evaluation in multivariate analysis: A test case study
2005 (English)In: Journal of Mathematical Modelling and Algorithms, ISSN 1570-1166, E-ISSN 1572-9214, Vol. 4, no 3, p. 289-305Article in journal (Refereed)
Abstract [en]

We have used different multivariate analysis methods to estimate quantities in the fields of food control and atmospheric remote sensing. In order to estimate the uncertainties in these estimates we studied analytical as well as non-parametric numerical methods. The methods have been evaluated by comparison between obtained results and independent sets of measurements. We present one test case from each field, including results, where these methods have been applied. For the food control test case reduced chi-squared (? ?2) of approximately unity indicate that both the analytical and numerical methods used for uncertainty estimation produce uncertainties of reasonable size. In the atmospheric remote sensing test case, a ??2 = 46 indicated that the uncertainties from the numerical method were far too small, whereas a ??2 = 1.5 indicate that the size of the analytically determined uncertainties can represent the size of the "true" errors. © Springer 2005.

Place, publisher, year, edition, pages
2005. Vol. 4, no 3, p. 289-305
Keywords [en]
Food Engineering
Keywords [sv]
Livsmedelsteknik
National Category
Food Science
Identifiers
URN: urn:nbn:se:ri:diva-9007DOI: 10.1007/s10852-005-9005-2OAI: oai:DiVA.org:ri-9007DiVA, id: diva2:966881
Available from: 2016-09-08 Created: 2016-09-08 Last updated: 2017-11-21Bibliographically approved

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Journal of Mathematical Modelling and Algorithms
Food Science

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