Change-Point Detection Under Dependence Based on Two-Sample U-Statistics

DOI10.1007/978-1-4939-3076-0_12zbMath1365.62333arXiv1304.2479OpenAlexW1499502832MaRDI QIDQ5272949

Isabel García, Roland Fried, Martin Wendler, Herold G. Dehling

Publication date: 5 July 2017

Published in: Asymptotic Laws and Methods in Stochastics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1304.2479

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Sequential statistical analysis (62L10) Functional limit theorems; invariance principles (60F17) Non-Markovian processes: hypothesis testing (62M07)

Related Items (13)

On change-points tests based on two-samples \(U\)-statistics for weakly dependent observations ⋮ A comparison of single and multiple changepoint techniques for time series data ⋮ Change-point detection based on weighted two-sample U-statistics ⋮ Asymptotic delay times of sequential tests based on \(U\)-statistics for early and late change points ⋮ Testing for change in mean for associated random variables ⋮ Testing equality of a large number of densities under mixing conditions ⋮ Dependent multiplier bootstraps for non-degenerate \(U\)-statistics under mixing conditions with applications ⋮ A weighted U-statistic based change point test for multivariate time series ⋮ Convergence of \(U\)-processes in Hölder spaces with application to robust detection of a changed segment ⋮ A tail adaptive approach for change point detection ⋮ Convergence of the empirical two-sample \(U\)-statistics with \(\beta\)-mixing data ⋮ Scan B-statistic for kernel change-point detection ⋮ Robust discrimination between long‐range dependence and a change in mean

Cites Work

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