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Convergence of U-processes in Holder spaces with application to robust detection of a changed segment

机译:持有者空间中的U-Forparation融合,应用于鲁棒检测改变的段

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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 Holder spaces. We also study the finite sample behavior via simulations and apply the statistic to a real data example.
机译:为了在时间序列中检测改变的段(所谓的疫情变化),经常使用CUSUM统计的变体。 然而,它们对数据中的异常值敏感,并且对于重型数据不对井表现良好,特别是当短片在测试统计中获得高重量时。 我们将基于Wilcoxon统计的流行病变化的强大测试统计数据。 为了研究他们的渐近行为,我们证明了持有人空间中的U-Forparation的功能限制定理。 我们还通过模拟研究有限的样本行为,并将统计信息应用于实际数据示例。

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