Change-point detection under dependence based on two-sample U-statistics
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Date
2013-04-23
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Abstract
We study the detection of change-points in time series. The classical CUSUM
statistic for detection of jumps in the mean is known to be sensitive to outliers. We thus
propose a robust test based on the Wilcoxon two-sample test statistic. The asymptotic
distribution of this test can be derived from a functional central limit theorem for two-sample
U-statistics. We extend a theorem of Csorgo and Horvath to the case of dependent
data.
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Keywords
change-point problems, two-sample U-statistics, weakly dependent data