The Identification of Multiple Outliers in Online Monitoring Data

dc.contributor.author	Bauer, Marcus	de
dc.contributor.author	Gather, Ursula	de
dc.contributor.author	Imhoff, Michael	de
dc.date.accessioned	2004-12-06T18:40:41Z
dc.date.available	2004-12-06T18:40:41Z
dc.date.issued	1999	de
dc.description.abstract	We present a robust graphical procedure for routine detection of isolated and patchy outliers in univariate time series. This procedure is suitable for retrospective as well as for online identification of outliers. It is based on a phase space reconstruction of the time series which allows to regard the time series as a multivariate sample with identically distributed but non independent observations. Thus, multivariate outlier identifiers can be transfered into the context of time series which is done here. Some applications to online monitoring data from intensive care are given.	en
dc.format.extent	1433344 bytes
dc.format.extent	531747 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/4965
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-5419
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject	multivariate sample	en
dc.subject	online monitoring	en
dc.subject	outlier identification	en
dc.subject	phase space reconstruction	en
dc.subject	process control	en
dc.subject	time series	en
dc.subject.ddc	310	de
dc.title	The Identification of Multiple Outliers in Online Monitoring Data	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access

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