5 papers
Inference for Forecasting Accuracy: Pooled versus Individual Estimators in High-dimensional Panel Data
Tim Kutta, Martin Schumann, Holger Dette
Panels with large time and cross-sectional dimensions are a key data structure in social sciences and other fields. A central question in panel data analysis is whether…
Multiscale Change Point Detection for Functional Time Series
Tim Kutta, Holger Dette, Shixuan Wang
We study the problem of detecting and localizing multiple changes in the mean parameter of a Banach space-valued time series. The goal is to construct a collection of narrow confid…
Monitoring Violations of Differential Privacy over Time
Önder Askin, Tim Kutta, Holger Dette
Auditing differential privacy has emerged as an important area of research that supports the design of privacy-preserving mechanisms. Privacy audits help to obtain empirical estima…
A New Two-Sample Test for Covariance Matrices in High Dimensions: U-Statistics Meet Leading Eigenvalues
Thomas Lam, Nina Dörnemann, Holger Dette
We propose a two-sample test for covariance matrices in the high-dimensional regime, where the dimension diverges proportionally to the sample size. Our hybrid test combines a Frob…
General-Purpose -DP Estimation and Auditing in a Black-Box Setting
Önder Askin, Holger Dette, Martin Dunsche +4
In this paper we propose new methods to statistically assess -Differential Privacy (-DP), a recent refinement of differential privacy (DP) that remedies certain weaknesses of…