Showing stat.MEShow all
3 papers · 1 filter
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…
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…