Outliers in multivariate time series

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dc.contributor.author Tsay, Ruey S.
dc.contributor.author Peña, Daniel
dc.contributor.author Pankratz, Alan E.
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2010-01-07T11:15:43Z
dc.date.available 2010-01-07T11:15:43Z
dc.date.issued 1998-12
dc.identifier.uri http://hdl.handle.net/10016/6285
dc.description.abstract This paper considers outliers in multivariate time series analysis. It generalizes four types of disturbances commonly used in the univariate time series analysis to the multivariate case, and investigates dynamic effects of a multivariate outlier on individual components if marginal models are used. An innovational outlier of a vector series can introduce a patch of outliers for the marginal component models. The paper also proposes an iterative procedure to detect and handle multiple outliers. By comparing and contrasting results of univariate and multivariate outlier detections, one can gain insights into the characteristics of an outlier. An outlier in a component series mayor may not have significant impacts on the other components. We use real examples to demonstrate the proposed analysis.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 98-96-42
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Additive outlier
dc.subject.other innovational outlier
dc.subject.other level shift
dc.subject.other temporary change
dc.title Outliers in multivariate time series
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
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