activity
20242026
collaborators

8 papers

math.ST2026

Goodness-of-Fit Testing for Groupwise Spherical Error Structures

Daria Tieplova, Nina Dörnemann, Tim Kutta

The analysis of large data panels is important in econometrics and beyond. Prediction and inference methods for such data typically rely on simplifying model assumptions for the co…

math.ST2026

Online Change-Point Monitoring for Object-valued Time Series

Yi Zhang, Tim Kutta, Xiaofeng Shao

We develop closed- and open-end procedures for monitoring changes in the marginal distribution of object-valued time series. The method combines two distance-based Hilbert-space em…

stat.ME2026

Change Point Detection and Localization in High-Dimensional Time Series

Patrick Bastian, Daria Tieplova, Nina Dörnemann +1

We present new inference tools for change point detection in high-dimensional time series. We discuss two distinct statistical applications: First, sequential change point testing…

stat.ME2026

Does PCA Work for Rough Functional Data?

Tim Kutta, Nina Dörnemann, Piotr Kokoszka

Functional data analysis is concerned with the analysis of infinite-dimensional data functions. Functional principal component analysis (FPCA) is a key method to obtain finite-dime…

math.OC2026

Iterative Data-Consistent Inversion with Multiple Push-forward Constraints

Tianyi Jiang, Troy Butler, Timothy Wildey +2

A foundational challenge in uncertainty quantification involves estimating a probability measure on the space of uncertain parameters such that its push-forward through a computati…

math.ST2025

Monitoring for a Phase Transition in a Time Series of Wigner Matrices

Nina Dörnemann, Piotr Kokoszka, Tim Kutta +1

We develop methodology and theory for the detection of a phase transition in a time-series of high-dimensional random matrices. In the model we study, at each time point \( t = 1,2…

math.ST2025

Prokhorov Metric Convergence of the Partial Sum Process for Reconstructed Functional Data

Tim Kutta, Piotr Kokoszka

Motivated by applications in functional data analysis, we study the partial sum process of sparsely observed, random functions. A key novelty of our analysis are bounds for the dis…

stat.ME2024

Detection of a structural break in intraday volatility pattern

Piotr Kokoszka, Tim Kutta, Neda Mohammadi +2

We develop theory leading to testing procedures for the presence of a change point in the intraday volatility pattern. The new theory is developed in the framework of Functional Da…