Hatzfeld, Christian ; Bilz, Johannes ; Schlemmer, Sascha ; Adolf, Jan-Eric ; Gu, Yangyang ; Elgner, Steffen ; Kupnik, Mario (2017)
Residual Analysis to Compare Measurement Series’ Differences with Significance and Size Measures.
IEEE SENSORS. Glasgow
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Current methods to compare measurement series are based on the comparison of multiple measurement points or fit parameters. These approaches depend on the quality of the fit and are prone to type I error accumulation, when standard statistical tests are used for evaluation. In this work, we present an approach based on a two-sample Kolmogorov-Smirnov test of residuals of data series to a fit in order to assess measurement series differences. This approach does neither rely on physical accurate model functions nor equal sample sizes or variances. It provides comparable measures for data differences as well as a reliability measure of the assessment. It is validated with a Monte Carlo simulation. Applications include the comparison of measurement series with diverse sampling rates or the comparison of measurements without clearly distinguishable properties.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Hatzfeld, Christian ; Bilz, Johannes ; Schlemmer, Sascha ; Adolf, Jan-Eric ; Gu, Yangyang ; Elgner, Steffen ; Kupnik, Mario |
| Art des Eintrags: | Bibliographie |
| Titel: | Residual Analysis to Compare Measurement Series’ Differences with Significance and Size Measures |
| Sprache: | Englisch |
| Publikationsjahr: | 29 Oktober 2017 |
| Veranstaltungstitel: | IEEE SENSORS |
| Veranstaltungsort: | Glasgow |
| Kurzbeschreibung (Abstract): | Current methods to compare measurement series are based on the comparison of multiple measurement points or fit parameters. These approaches depend on the quality of the fit and are prone to type I error accumulation, when standard statistical tests are used for evaluation. In this work, we present an approach based on a two-sample Kolmogorov-Smirnov test of residuals of data series to a fit in order to assess measurement series differences. This approach does neither rely on physical accurate model functions nor equal sample sizes or variances. It provides comparable measures for data differences as well as a reliability measure of the assessment. It is validated with a Monte Carlo simulation. Applications include the comparison of measurement series with diverse sampling rates or the comparison of measurements without clearly distinguishable properties. |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Elektromechanische Konstruktionen (aufgelöst 18.12.2018) 18 Fachbereich Elektrotechnik und Informationstechnik > Mikrotechnik und Elektromechanische Systeme 18 Fachbereich Elektrotechnik und Informationstechnik > Mess- und Sensortechnik 18 Fachbereich Elektrotechnik und Informationstechnik |
| Hinterlegungsdatum: | 07 Nov 2017 08:41 |
| Letzte Änderung: | 07 Nov 2017 08:41 |
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