24 citations · 28 across the 5 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
stat.ME2026
Testing Covariance Separability in High Dimensions
Tomas Masak, Marcus Mayrhofer, Una Radojičić
Separability is an important structural assumption often placed on the covariance when working with matrix-variate data, because it greatly simplifies both interpretation and compu…
stat.ME2026
Explainable Outlier Detection for Multivariate Functional Data
Marcus Mayrhofer, Una Radojičić, Horst Lewitschnig +1
This work addresses the challenges of robust covariance estimation and interpretable outlier detection for multivariate functional data with separable covariance structure. We deve…