2 papers
stat.ME2025
Highly robust factored principal component analysis for matrix-valued outlier accommodation and explainable detection via matrix minimum covariance determinant
Wenhui Wu, Changchun Shang, Jianhua Zhao +2
Principal component analysis (PCA) is a classical and widely used method for dimensionality reduction, with applications in data compression, computer vision, pattern recognition,…
stat.ME2025
Matrix Healy Plot: A Practical Tool for Visual Assessment of Matrix-Variate Normality
Fen Jiang, Jianhua Zhao, Changchun Shang +3
Matrix-valued data, where each observation is represented as a matrix, frequently arises in various scientific disciplines. Modeling such data often relies on matrix-variate normal…