7 papers
Computationally tractable nonparametric bootstrap of high-dimensional sample covariance matrices
Holger Dette, Angelika Rohde
We introduce a new `` out of '' sampling-with-replace\-ment bootstrap for eigenvalue statistics of high-dimensional sample covariance matrices based on indepen…
Sequential Eigenvalue Statistics for Change-Point Detection in Covariance Matrices
Nina Dörnemann, Holger Dette
Testing for change points in sequences of covariance matrices is an important and equally challenging problem in statistical methodology with applications in various fields. Motiva…
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
Ãnder 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…
General-Purpose -DP Estimation and Auditing in a Black-Box Setting
Ãnder 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…