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On-line change-point detection (for state space models) using multi-process Kalman filters

✍ Scribed by Martin Daumer; Markus Falk


Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
650 KB
Volume
284
Category
Article
ISSN
0024-3795

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✦ Synopsis


In this Paper we show how to use an on-line algorithm based on a multi-process-Kalman-filterextending ideas described in Whittaker and Frühwirth-Sehnatter (J. Whittaker, Frühwirth-Sehnatter, Appl. Stat. 43 (4) (1994)) -to detect sequential Change-Points in noisy time series. We focus on types of Change-Points typically arising in biomedical Signals, i.e. jumps or drifts in nonstationary time series possibly corrupted by embedded outliers. The algorithm has been implemented in a program written in Matlab 5.0 and was tested using vital Parameters recorded during surgical procedures performed at the