Robust online scale estimation in time series

dc.contributor.authorCroux, Christophe
dc.contributor.authorGather, Ursula
dc.contributor.authorGelper, Sarah
dc.contributor.authorSchettlinger, Karen
dc.date.accessioned2007-05-25T12:39:28Z
dc.date.available2007-05-25T12:39:28Z
dc.date.issued2007-05-25T12:39:28Z
dc.description.abstractThis paper presents variance extraction procedures for univariate time series. The volatility of a times series is monitored allowing for non-linearities, jumps and outliers in the level. The volatility is measured using the height of triangles formed by consecutive observations of the time series. This idea was proposed by Rousseeuw and Hubert (1996, Regression-free and robust estimation of scale for bivariate data, Computational Statistics and Data Analysis, 21, 67{85) in the bivariate setting. This paper extends their procedure to apply for online scale estimation in time series analysis. The statistical properties of the new methods are derived and finite sample properties are given. A financial and a medical application illustrate the use of the procedures.en
dc.identifier.urihttp://hdl.handle.net/2003/24318
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15812
dc.language.isoende
dc.subjectBreakdown pointen
dc.subjectInfluence functionen
dc.subjectOnline monitoringen
dc.subjectOutliersen
dc.subjectRobust scale estimationen
dc.subject.ddc004
dc.titleRobust online scale estimation in time seriesen
dc.typeTexten
dc.type.publicationtypereporten
dcterms.accessRightsopen access

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