A new approach for open-end sequential change point monitoring
- 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.
| Author: | Josua GösmannGND, Tobias KleyORCiDGND, Holger DetteORCiDGND |
|---|---|
| URN: | urn:nbn:de:hbz:294-99931 |
| DOI: | https://doi.org/10.1111/jtsa.12555 |
| Parent Title (English): | Journal of time series analysis |
| Publisher: | Wiley |
| Place of publication: | Hoboken, New Jersey |
| Document Type: | Article |
| Language: | English |
| Date of Publication (online): | 2023/06/23 |
| Date of first Publication: | 2020/08/11 |
| Publishing Institution: | Ruhr-Universität Bochum, Universitätsbibliothek |
| Tag: | Change point analysis; open-end procedures; sequential monitoring |
| Volume: | 42 |
| Issue: | 1 |
| First Page: | 63 |
| Last Page: | 84 |
| Note: | Dieser Beitrag ist auf Grund des DEAL-Wiley-Vertrages frei zugänglich. |
| Institutes/Facilities: | Lehrstuhl für Stochastik |
| Dewey Decimal Classification: | Naturwissenschaften und Mathematik / Mathematik |
| open_access (DINI-Set): | open_access |
| faculties: | Fakultät für Mathematik |
| Licence (English): |  Creative Commons - CC BY 4.0 - Attribution 4.0 International |
