Online Monitoring with Local Smoothing Methods and Adaptive Ridging

Einbeck, Jochen; Kauermann, Goeran

doi:10.1080/0094965031000104332

Online Monitoring with Local Smoothing Methods and Adaptive Ridging

Einbeck, Jochen; Kauermann, Goeran

Authors

Professor Jochen Einbeck jochen.einbeck@durham.ac.uk
Professor

Goeran Kauermann

Abstract

We consider online monitoring of sequentially arising data as e.g. met in clinical information systems. The general focus thereby is to detect breakpoints, i.e. timepoints where the measurement series suddenly changes the general level. The method suggested is based on local estimation. In particular, local linear smoothing is combined by ridging with local constant smoothing. The procedure is demonstrated by examples and compared with other available online monitoring routines.

Citation

Einbeck, J., & Kauermann, G. (2003). Online Monitoring with Local Smoothing Methods and Adaptive Ridging. Journal of Statistical Computation and Simulation, 73(12), 913-929. https://doi.org/10.1080/0094965031000104332

Journal Article Type	Article
Publication Date	Dec 1, 2003
Deposit Date	Feb 13, 2015
Publicly Available Date	Feb 13, 2015
Journal	Journal of Statistical Computation and Simulation
Print ISSN	0094-9655
Electronic ISSN	1563-5163
Publisher	Taylor and Francis Group
Peer Reviewed	Peer Reviewed
Volume	73
Issue	12
Pages	913-929
DOI	https://doi.org/10.1080/0094965031000104332
Keywords	Breakpoint detection, Online monitoring, Local linear smoothing, Ridging

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Accepted Journal Article (391 Kb)
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Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of statistical computation and simulation in 2003, and available online at: http://dx.doi.org/10.1080/0094965031000104332