Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/288585 
Year of Publication: 
2020
Citation: 
[Journal:] Statistical Papers [ISSN:] 1613-9798 [Volume:] 61 [Issue:] 4 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2020 [Pages:] 1409-1435
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
To detect a changed segment (so called epidemic changes) in a time series, variants of the CUSUM statistic are frequently used. However, they are sensitive to outliers in the data and do not perform well for heavy tailed data, especially when short segments get a high weight in the test statistic. We will present a robust test statistic for epidemic changes based on the Wilcoxon statistic. To study their asymptotic behavior, we prove functional limit theorems for U-processes in Hölder spaces. We also study the finite sample behavior via simulations and apply the statistic to a real data example.
Subjects: 
Wilcoxon statistic
Epidemic change
Functional central limit theorem
Hölder space
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
Document Version: 
Published Version

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