Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
418100 | Computational Statistics & Data Analysis | 2007 | 12 Pages |
Abstract
Abrupt shifts in the level of a time series represent important information and should be preserved in statistical signal extraction. Various rules for detecting level shifts that are resistant to outliers and which work with only a short time delay are investigated. 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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Roland Fried,