Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/22566 
Year of Publication: 
2004
Series/Report no.: 
Technical Report No. 2004,53
Publisher: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
In intensive care, time series of vital parameters have to be analysed online, i.e. without any time delay, since there may be serious consequences for the patient otherwise. Such time series show trends, slope changes and sudden level shifts, and they are overlaid by strong noise and many measurement artefacts. The development of update algorithms and the resulting increase in computational speed allows to apply robust regression techniques to moving time windows for online signal extraction. By simulations and applications we compare the performance of least median of squares, least trimmed squares, repeated median and deepest regression for online signal extraction.
Subjects: 
Robust filtering
least median of squares
least trimmed squares
repeated median
deepest regression
breakdown point
Document Type: 
Working Paper

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