Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/36580 
Year of Publication: 
2007
Series/Report no.: 
Technical Report No. 2007,38
Publisher: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
We introduce robust regression-based online filters for multivariate time series and discuss their performance in real time signal extraction settings. We focus on methods that can deal with time series exhibiting patterns such as trends, level changes, outliers and a high level of noise as well as periods of a rather steady state. In particular, the data may be measured on a discrete scale which often occurs in practice. Our new filter is based on a robust two-step online procedure. We investigate its relevant properties and its performance by means of simulations and a medical application.
Subjects: 
Multivariate time series
signal extraction
robust regression
online methods
Document Type: 
Working Paper

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