Variance changes detection in multivariate time series

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dc.contributor.author Galeano, Pedro
dc.contributor.author Peña, Daniel
dc.date.accessioned 2006-11-09T10:55:50Z
dc.date.available 2006-11-09T10:55:50Z
dc.date.issued 2004-02
dc.identifier.uri http://hdl.handle.net/10016/209
dc.description.abstract This paper studies the detection of step changes in the variances and in the correlation structure of the components of a vector of time series. Two procedures are considered. The first is based on the likelihood ratio test and the second on cusum statistics. These two procedures are compared in a simulation study and we conclude that the cusum procedure is more powerful. The procedures are illustrated in two examples.R
dc.format.extent 575634 bytes
dc.format.mimetype application/pdf
dc.language.iso eng
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 2004-05
dc.title Variance changes detection in multivariate time series
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws041305
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