Package: IALS 0.1.3

Ran Zhao

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) <arxiv:2301.00360>.

Authors:Yong He [aut], Ran Zhao [aut, cre], Wen-Xin Zhou [aut]

IALS_0.1.3.tar.gz
IALS_0.1.3.tar.gz(r-4.5-noble)IALS_0.1.3.tar.gz(r-4.4-noble)
IALS_0.1.3.tgz(r-4.4-emscripten)IALS_0.1.3.tgz(r-4.3-emscripten)
IALS.pdf |IALS.html✨
IALS/json (API)

# Install 'IALS' in R:
install.packages('IALS', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 176 downloads 3 exports 8 dependencies

Last updated 1 years agofrom:0c174b1fd4. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 13 2025
R-4.5-linuxOKMar 13 2025
R-4.4-linuxOKMar 13 2025

Exports:DistanceIALSKIALS

Dependencies:HDMFAlatticeMASSMatrixpracmaRcppRcppEigenRSpectra

Citation

To cite package ‘IALS’ in publications use:

He Y, Zhao R, Zhou W (2024). IALS: Iterative Alternating Least Square Estimation for Large-Dimensional Matrix Factor Model. R package version 0.1.3, https://CRAN.R-project.org/package=IALS.

Corresponding BibTeX entry: 

  @Manual{,
    title = {IALS: Iterative Alternating Least Square Estimation for
      Large-Dimensional Matrix Factor Model},
    author = {Yong He and Ran Zhao and Wen-Xin Zhou},
    year = {2024},
    note = {R package version 0.1.3},
    url = {https://CRAN.R-project.org/package=IALS},
  }