Package: IALS
Type: Package
Title: Iterative Alternating Least Square Estimation for
        Large-Dimensional Matrix Factor Model
Version: 0.1.3
Author: Yong He [aut],
  Ran Zhao [aut, cre],
  Wen-Xin Zhou [aut]
Authors@R: c(person("Yong", "He", role = "aut"),
	     person("Ran", "Zhao", role = c("aut","cre"), email="Zhaoran@mail.sdu.edu.cn"),
	     person("Wen-Xin", "Zhou", role="aut"))
Maintainer: Ran Zhao <Zhaoran@mail.sdu.edu.cn>
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>.
License: GPL-2 | GPL-3
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: RSpectra, pracma, HDMFA
NeedsCompilation: no
Packaged: 2024-02-16 11:31:24 UTC; 赵冉
Repository: CRAN
Date/Publication: 2024-02-16 11:50:07 UTC
Built: R 4.6.0; ; 2026-04-27 17:35:47 UTC; unix
