IALS

Description

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) <arXiv:2301.00360>.

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Maintainer: ‘Ran Zhao <Zhaoran@mail.sdu.edu.cn>’

The Description field contains
  in He et al. (2023) <arXiv:2301.00360>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

Maintainer: ‘Ran Zhao <Zhaoran@mail.sdu.edu.cn>’

The Description field contains
  in He et al. (2023) <arXiv:2301.00360>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

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Maintainer: ‘Ran Zhao <Zhaoran@mail.sdu.edu.cn>’

The Description field contains
  in He et al. (2023) <arXiv:2301.00360>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

Maintainer: ‘Ran Zhao <Zhaoran@mail.sdu.edu.cn>’

The Description field contains
  in He et al. (2023) <arXiv:2301.00360>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

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