4 papers · 1 filter
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…
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…
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…