Robust estimation of (partial) autocorrelation

dc.contributor.author	Dürre, Alexander
dc.contributor.author	Fried, Roland
dc.contributor.author	Liboschik, Tobias
dc.date.accessioned	2014-04-08T10:44:15Z
dc.date.available	2014-04-08T10:44:15Z
dc.date.issued	2014-04-08
dc.description.abstract	The autocorrelation function (acf) and the partial autocorrelation function (pacf) are elementary tools of linear time series analysis. The sensitivity of the conventional sample acf and pacf to outliers is well known. We review robust estimators and evaluate their performances in different data situations considering Gaussian scenarios with and without outliers in a simulation study.	en
dc.identifier.uri	http://hdl.handle.net/2003/33011
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-13701
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823;12/2014
dc.subject	autocovariance	en
dc.subject	correlogram	en
dc.subject	time series	en
dc.subject	outliers	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.title	Robust estimation of (partial) autocorrelation	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access
eldorado.dnb.deposit	true	de

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