  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 H\"older spaces. We also study the finite
sample behavior via simulations and apply the statistic to a real data example.
