Autor(en): | Dette, Holger Gösmann, Josua |
Titel: | A likelihood ratio approach to sequential change point detection |
Sprache (ISO): | en |
Zusammenfassung: | In this paper we propose a new approach for sequential monitoring of a parameter of a d-dimensional time series. We consider a closed-end-method, which is motivated by the likelihood ratio test principle and compare the new method with two alternative procedures. We also incorporate self-normalization such that estimation of the longrun variance is not necessary. We prove that for a large class of testing problems the new detection scheme has asymptotic level a and is consistent. The asymptotic theory is illustrated for the important cases of monitoring a change in the mean, variance and correlation. By means of a simulation study it is demonstrated that the new test performs better than the currently available procedures for these problems. |
Schlagwörter: | change point analysis likelihood ratio principle sequential monitoring self-normalization |
Schlagwörter (RSWK): | Change-point-Problem Sequenzieller Test Likelihood-Quotienten-Test |
URI: | http://hdl.handle.net/2003/36782 http://dx.doi.org/10.17877/DE290R-18783 |
Erscheinungsdatum: | 2018 |
Enthalten in den Sammlungen: | Sonderforschungsbereich (SFB) 823 |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
---|---|---|---|---|
DP_0218_SFB823_Dette_Gösmann.pdf | DNB | 568.69 kB | Adobe PDF | Öffnen/Anzeigen |
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