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) doi:10.48550/arXiv.2301.00360.
- Version0.1.3
- R version≥ 4.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release02/16/2024
Team
Ran Zhao
Wen-Xin Zhou
Show author detailsRolesAuthorYong He
Show author detailsRolesAuthor
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Last 30 days
This package has been downloaded 159 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
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Last 365 days
This package has been downloaded 1,939 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jul 31, 2024 with 22 downloads.
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- Imports3 packages