7 citations · 13 across the 4 of their papers we have counts for
5 papers
Cellwise, Blockwise, and Casewise Robust Multiblock PCA for Sustainable and Inclusive Wellbeing in the EU
Arthur Daisomont, Fabio Centofanti, Mia Hubert
Gross Domestic Product (GDP) is widely used to guide economic and social decision-making, but it provides only a partial view of wellbeing. For this reason, the European Union (EU)…
Cellwise and Casewise Robust Covariance in High Dimensions
Fabio Centofanti, Mia Hubert, Peter J. Rousseeuw
The sample covariance matrix is a cornerstone of multivariate statistics, but it is highly sensitive to outliers. These can be casewise outliers, such as cases belonging to a diffe…
Robust discriminant analysis
Mia Hubert, Jakob Raymaekers, Peter J. Rousseeuw
Discriminant analysis (DA) is one of the most popular methods for classification due to its conceptual simplicity, low computational cost, and often solid performance. In its stand…
Robust Principal Components by Casewise and Cellwise Weighting
Fabio Centofanti, Mia Hubert, Peter J. Rousseeuw
Principal component analysis (PCA) is a fundamental tool for analyzing multivariate data. Here the focus is on dimension reduction to the principal subspace, characterized by its p…
Multivariate Singular Spectrum Analysis by Robust Diagonalwise Low-Rank Approximation
Fabio Centofanti, Mia Hubert, Biagio Palumbo +1
Multivariate Singular Spectrum Analysis (MSSA) is a powerful and widely used nonparametric method for multivariate time series, which allows the analysis of complex temporal data f…