IALS: Iterative Alternating Least Square Estimation forLarge-Dimensional Matrix Factor Model
The matrix factor model has drawn growing attention for its advantage in achieving two-directional dimension reduction simultaneously for matrix-structured observations. In contrast to the Principal Component Analysis (PCA)-based methods, we propose a simple Iterative Alternating Least Squares (IALS) algorithm for matrix factor model, see the details in He et al. (2023) <doi:10.48550/arXiv.2301.00360>.
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