From the 1 of 9 linked papers with an AI index.
9 papers
Selfnormalization for relevant inference with supremum-type statistics
Patrick Bastian
The paper proposes a self‑normalized method for testing relevant changes in functional time series measured by the supremum norm, using a smooth log‑sum‑exp approximation and bias‑…
Differentially private testing for relevant dependencies in high dimensions
Patrick Bastian, Holger Dette, Martin Dunsche
We investigate the problem of detecting dependencies between the components of a high-dimensional vector. Our approach advances the existing literature in two important respects. F…
Monitoring Time Series for Relevant Changes
Patrick Bastian, Tim Kutta, Rupsa Basu +1
We consider the problem of sequentially testing for changes in the mean parameter of a time series, compared to a benchmark period. Most tests in the literature focus on the null h…
SILENT: A New Lens on Statistics in Software Timing Side Channels
Martin Dunsche, Patrick Bastian, Marcel Maehren +5
Cryptographic research takes software timing side channels seriously. Approaches to mitigate them include constant-time coding and techniques to enforce such practices. However, re…
Multiscale detection of practically significant changes in a gradually varying time series
Patrick Bastian, Holger Dette
In many change point problems it is reasonable to assume that compared to a benchmark at a given time point the properties of the observed stochastic process change gradually…
Detecting relevant dependencies under measurement error with applications to the analysis of planetary system evolution
Patrick Bastian, Nicolai Bissantz
Exoplanets play an important role in understanding the mechanics of planetary system formation and orbital evolution. In this context the correlations of different parameters of th…