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Mathematische Modellierung und Datenanalyse

Fachbereich 8.4

Publikations Einzelansicht


Titel: Bayesian regression versus application of least squares—an example
Autor(en): C. Elster and G. Wübbeler
Journal: Metrologia
Jahr: 2016
Band: 53
Ausgabe: 1
Seite(n): S10
DOI: 10.1088/0026-1394/53/1/S10
Web URL: http://stacks.iop.org/0026-1394/53/i=1/a=S10
Marker: 8.4, 8.42, Unsicherheit, Regression
Zusammenfassung: Regression is an important task in metrology and least-squares methods are often applied in this context. Bayesian inference provides an alternative that can take into account available prior knowledge. We illustrate similarities and differences of the two approaches in terms of a particular nonlinear regression problem. The impact of prior knowledge utilized in the Bayesian regression depends on the amount of information contained in the data, and by considering data sets with different signal-to-noise ratios the relevance of the employed prior knowledge for the results is investigated. In addition, properties of the two approaches are explored in the context of the particular example.

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