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On the robust detection of edges in time series filtering

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  • Fried, Roland

Abstract

Abrupt shifts in the level of a time series represent important information and should be preserved in statistical signal extraction. We investigate rules for detecting level shifts that are resistant to outliers and which work with only a short time delay. The properties of robustified versions of the t-test for two independent samples and its non-parametric alternatives are elaborated under different types of noise. Trimmed t-tests, median comparisons, robustified rank and ANOVA tests based on robust scale estimators are compared.

Suggested Citation

  • Fried, Roland, 2007. "On the robust detection of edges in time series filtering," Technical Reports 2007,20, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200720
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    References listed on IDEAS

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    1. Achim Zeileis, 2005. "A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 445-466.
    2. Fried, Roland & Gather, Ursula, 2007. "On rank tests for shift detection in time series," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 221-233, September.
    3. P.J. Rousseeuw & A.M. Leroy, 1988. "A robust scale estimator based on the shortest half," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 42(2), pages 103-116, June.
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