Change-point detection based on weighted two-sample U-statistics

Abstract

We investigate the large-sample behavior of change-point tests based on weighted two-sample U-statistics, in the case of short-range dependent data. Under some mild mixing conditions, we establish convergence of the test statistic to an extreme value distribution. A simulation study shows that the weighted tests are superior to the non-weighted versions when the change-point occurs near the boundary of the time interval, while they loose power in the center.

References in corpus (3)

• Estimation of the variance of partial sums of dependent processes
• Adaptive Inference for Change Points in High-Dimensional Data
• Asymptotic delay times of sequential tests based on U-statistics for early and late change points