activity
20182025
most citedGradual changes in functional time series

1 citations · 2 across the 10 of their papers we have counts for

collaborators

10 papers

math.ST2025

Differentially private testing for relevant dependencies in high dimensions

Patrick Bastian, Holger Dette, Martin Dunsche

We investigate the problem of detecting dependencies between the components of a high-dimensional vector. Our approach advances the existing literature in two important respects. F…

stat.ME2025

Monitoring Time Series for Relevant Changes

Patrick Bastian, Tim Kutta, Rupsa Basu +1

We consider the problem of sequentially testing for changes in the mean parameter of a time series, compared to a benchmark period. Most tests in the literature focus on the null h…

cs.CR2025

SILENT: A New Lens on Statistics in Software Timing Side Channels

Martin Dunsche, Patrick Bastian, Marcel Maehren +5

Cryptographic research takes software timing side channels seriously. Approaches to mitigate them include constant-time coding and techniques to enforce such practices. However, re…

stat.ME2025

Multiscale detection of practically significant changes in a gradually varying time series

Patrick Bastian, Holger Dette

In many change point problems it is reasonable to assume that compared to a benchmark at a given time point the properties of the observed stochastic process change gradually…

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…

stat.ME2025

Uniform confidence bands for joint angles across different fatigue phases

Patrick Bastian, Rupsa Basu, Holger Dette

We develop uniform confidence bands for the mean function of stationary time series as a post-hoc analysis of multiple change point detection in functional time series. In particul…

math.ST2024★ 1 cited

Gradual changes in functional time series

Patrick Bastian, Holger Dette

We consider the problem of detecting gradual changes in the sequence of mean functions from a not necessarily stationary functional time series. Our approach is based on the maximu…

math.ST2024

Balancing the edge effect and dimension of spectral spatial statistics under irregular sampling with applications to isotropy testing

Theresa Eckle, Anne van Delft, Holger Dette

We investigate distributional properties of a class of spectral spatial statistics under irregular sampling of a random field that is defined on , and use this to obt…

math.ST2023★ 1 cited

Multiple change point detection in functional data with applications to biomechanical fatigue data

Patrick Bastian, Rupsa Basu, Holger Dette

Injuries to the lower extremity joints are often debilitating, particularly for professional athletes. Understanding the onset of stressful conditions on these joints is therefore…

math.ST2018

A likelihood ratio approach to sequential change point detection for a general class of parameters

Holger Dette, Josua Gösmann

In this paper we propose a new approach for sequential monitoring of a parameter of a -dimensional time series, which can be estimated by approximately linear functionals of the…