Change-Point Detection under Dependence Based on Two-Sample U-Statistics
Statistics Theory
2013-04-10 v1 Statistics Theory
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.
Cite
@article{arxiv.1304.2479,
title = {Change-Point Detection under Dependence Based on Two-Sample U-Statistics},
author = {Herold Dehling and Roland Fried and Isabel García and Martin Wendler},
journal= {arXiv preprint arXiv:1304.2479},
year = {2013}
}