Robust repeated median regression in moving windows with data-adaptive width selection

dc.contributor.authorBorowski, Matthias
dc.contributor.authorFried, Roland
dc.date.accessioned2011-09-07T10:11:08Z
dc.date.available2011-09-07T10:11:08Z
dc.date.issued2011-09-07
dc.description.abstractOnline (also 'real-time' or 'sequential') signal extraction from noisy and outlier- interfered data streams is a basic but challenging goal. Fitting a robust Repeated Median (Siegel, 1982) regression line in a moving time window has turned out to be a promising approach (Davies et al., 2004; Gather et al., 2006; Schettlinger et al., 2006). The level of the regression line at the rightmost window position, which equates to the current time point in an online application, is then used as signal extraction. However, the choice of the window width has large impact on the signal extraction, and it is impossible to predetermine an optimal fixed window width for data streams which exhibit signal changes like level shifts and sudden trend changes. We therefore propose a robust test procedure for the online detection of such signal changes. An algorithm including the test allows for online window width adaption, meaning that the window width is chosen w.r.t. the current data situation at each time point. Comparison studies show that our new procedure outperforms an existing Repeated Median filter with automatic window width selection (Schettlinger et al., 2010).en
dc.identifier.urihttp://hdl.handle.net/2003/29071
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-13059
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;28/2011
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleRobust repeated median regression in moving windows with data-adaptive width selectionen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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