On the robust detection of edges in time series filtering
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Date
2007-07-13T12:03:00Z
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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, robusti-
fied rank and ANOVA tests based on robust scale estimators are compared.
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Keywords
Jumps, Outliers, Test resistance, Time series filtering