Control charts for the mean based on robust two-sample tests
| dc.contributor.author | Abbas, Sermad | |
| dc.contributor.author | Fried, Roland | |
| dc.date.accessioned | 2016-05-02T13:33:57Z | |
| dc.date.available | 2016-05-02T13:33:57Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | We propose and investigate robust control charts for the detection of sudden shifts in sequences of very noisy observations with a naturally slowly varying mean. They sequentially apply local two-sample tests for the location problem. Thus, no previous knowledge about the in-control behaviour is necessary. We identify critical values for the tests to achieve a desired in-control average run length (ARL_0) with extensive simulations. Control charts based on nonparametric tests or a randomization principle provide a satisfactory run length behaviour for different error distributions. They possess a nearly distribution-free ARL_0 and are fast in detecting present signal jumps in a time series. In our simulations and exemplary real-world applications from biosignal analysis, a test based on the two-sample Hodges-Lehmann estimator leads to very promising results regarding distribution independence, robustness and detection speed. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/34951 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-16999 | |
| dc.language.iso | en | de |
| dc.relation.ispartofseries | Discussion Paper / SFB823;21, 2016 | en |
| dc.subject | biosignal analysis | en |
| dc.subject | monitoring | en |
| dc.subject | two-sample tests | en |
| dc.subject | time series | en |
| dc.subject | robust control charts | en |
| dc.subject | change-point detection | en |
| dc.subject.ddc | 310 | |
| dc.subject.ddc | 330 | |
| dc.subject.ddc | 620 | |
| dc.title | Control charts for the mean based on robust two-sample tests | en |
| dc.type | Text | de |
| dc.type.publicationtype | workingPaper | de |
| dcterms.accessRights | open access |