Galeano, PedroPeña, Daniel2006-11-092006-11-092004-02http://hdl.handle.net/10016/209This 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.R575634 bytesapplication/pdfengVariance changes detection in multivariate time seriesworking paperEstadísticaopen accessws041305