6 papers · 1 filter
Monitoring for a Phase Transition in a Time Series of Wigner Matrices
Nina Dörnemann, Piotr Kokoszka, Tim Kutta +1
We develop methodology and theory for the detection of a phase transition in a time-series of high-dimensional random matrices. In the model we study, at each time point \( t = 1,2…
Two-Sample Covariance Inference in High-Dimensional Elliptical Models
Nina Dörnemann
We propose a two-sample test for large-dimensional covariance matrices in generalized elliptical models. The test statistic is based on a U-statistic estimator of the squared Frobe…
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…
Tracy-Widom, Gaussian, and Bootstrap: Approximations for Leading Eigenvalues in High-Dimensional PCA
Nina Dörnemann, Miles E. Lopes
Under certain conditions, the largest eigenvalue of a sample covariance matrix undergoes a well-known phase transition when the sample size and data dimension diverge propo…
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…
Linear spectral statistics of sequential sample covariance matrices
Nina Dörnemann, Holger Dette
Independent -dimensional vectors with independent complex or real valued entries such that , ,…