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20182026
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math.ST2026

Testing for Stable Intervals in Non-Stationary Time Series

Florian Heinrichs

Many time series are not stable over their full observation horizon, but may contain scientifically meaningful periods during which a signal remains stable up to a prescribed toler…

math.ST2026

A Functional Central Limit Theorem for Localized Partial Sums of Non-Stationary Time Series

Florian Heinrichs

A localized functional central limit theorem is established for kernel-weighted partial sum processes of piecewise locally stationary time series under geometric decay of the physi…

math.ST2025

Self-Normalization for CUSUM-based Change Detection in Locally Stationary Time Series

Florian Heinrichs

A new bivariate partial sum process for locally stationary time series is introduced and its weak convergence to a Brownian sheet is established. This construction enables the deve…

math.ST2025

Sequential Outlier Detection in Non-Stationary Time Series

Florian Heinrichs, Patrick Bastian, Holger Dette

A novel method for sequential outlier detection in non-stationary time series is proposed. The method tests the null hypothesis of ``no outlier'' at each time point, addressing the…

math.ST2020

A Portmanteau-type test for detecting serial correlation in locally stationary functional time series

Axel Bücher, Holger Dette, Florian Heinrichs

The Portmanteau test provides the vanilla method for detecting serial correlations in classical univariate time series analysis. The method is extended to the case of observations…

math.ST2020

A distribution free test for changes in the trend function of locally stationary processes

Holger Dette, Florian Heinrichs

In the common time series model with non-stationary errors we consider the problem of detecting a significant deviation of the mean function…