IALS
Iterative Alternating Least Square Estimation for Large-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)
- Version0.1.3
- R version≥ 4.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release02/16/2024
Team
Ran Zhao
Yong He
Show author detailsRolesAuthorWen-Xin Zhou
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- Depends1 package
- Imports3 packages