Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/230290
Authors: 
Gösmann, Josua
Kley, Tobias
Dette, Holger
Year of Publication: 
2020
Citation: 
[Journal:] Journal of Time Series Analysis [ISSN:] 1467-9892 [Volume:] [Issue:] [Pages:] n/a-n/a
Abstract: 
We propose a new sequential monitoring scheme for changes in the parameters of a multivariate time series. In contrast to procedures proposed in the literature which compare an estimator from the training sample with an estimator calculated from the remaining data, we suggest to divide the sample at each time point after the training sample. Estimators from the sample before and after all separation points are then continuously compared calculating a maximum of norms of their differences. For open‐end scenarios our approach yields an asymptotic level α procedure, which is consistent under the alternative of a change in the parameter. By means of a simulation study it is demonstrated that the new method outperforms the commonly used procedures with respect to power and the feasibility of our approach is illustrated by analyzing two data examples.
Subjects: 
Change point analysis
open‐end procedures
sequential monitoring
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
Document Version: 
Published Version

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