IALS: Iterative Alternating Least Square Estimation for Large-Dimensional Matrix Factor Model
Yong He, Ran Zhao, Wen‐Xin Zhou · 2024
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) .