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dc.contributor.authorEskildsen, Carl Emil Aae
dc.contributor.authorNæs, Tormod
dc.date.accessioned2020-11-13T09:59:31Z
dc.date.available2020-11-13T09:59:31Z
dc.date.created2020-07-27T09:43:13Z
dc.date.issued2020
dc.identifier.citationApplied Spectroscopy. 2020, 74 (7), 791-798.
dc.identifier.issn0003-7028
dc.identifier.urihttps://hdl.handle.net/11250/2687739
dc.description.abstractIn applied spectroscopy, the purpose of multivariate calibration is almost exclusively to relate analyte concentrations and spectroscopic measurements. The multivariate calibration model provides estimates of analyte concentrations based on the spectroscopic measurements. Predictive performance is often evaluated based on a mean squared error. While this average measure can be used in model selection, it is not satisfactory for evaluating the uncertainty of individual predictions. For a calibration, the uncertainties are sample specific. This is especially true for multivariate calibration, where interfering compounds may be present. Consider in-line spectroscopic measurements during a chemical reaction, production, etc. Here, reference values are not necessarily available. Hence, one should know the uncertainty of a given prediction in order to use that prediction for telling the state of the chemical reaction, adjusting the process, etc. In this paper, we discuss the influence of variance and bias on sample-specific prediction errors in multivariate calibration. We compare theoretical formulae with results obtained on experimental data. The results point towards the fact that bias contribution cannot necessarily be neglected when assessing sample-specific prediction ability in practice.
dc.language.isoeng
dc.subjectSample spesific uncertainty
dc.subjectSample spesific uncertainty
dc.subjectSpektroskopi
dc.subjectSpectroscopy
dc.subjectMultivariate calibration
dc.subjectMultivariate calibration
dc.titleSample-Specific Prediction Error Measures in Spectroscopy
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersion
dc.source.pagenumber791-798
dc.source.volume74
dc.source.journalApplied Spectroscopy
dc.source.issue7
dc.identifier.doi10.1177/0003702820913562
dc.identifier.cristin1820544
dc.relation.projectNofima AS: 201702
dc.relation.projectNorges forskningsråd: 262308
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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