8 papers
Simultaneous Inference for Partially Observed Functional Time Series
Patrick Bastian, Tim Kutta
Functional data analysis (FDA) provides statistical methods for analyzing samples of time-continuous stochastic processes. Measurements often arise in the form of sensor data for a…
Sequential Auditing for f-Differential Privacy
Tim Kutta, Martin Dunsche, Yu Wei +1
We present new auditors to assess Differential Privacy (DP) of an algorithm based on output samples. Such empirical auditors are common to check for algorithmic correctness and imp…
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…
TWIN: Two window inspection for online change point detection
Patrick Bastian, Tim Kutta
We propose a new class of sequential change point tests, both for changes in the mean parameter and in the overall distribution function. The methodology builds on a two-window ins…
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…