Package: CMGFM
Type: Package
Title: Interpretable Multi-Omics Representation Learning via
        Covariate-Augumented Generalized Factor Model
Version: 1.1
Date: 2024-06-21
Authors@R: 
    c(person(given = "Wei",
             family = "Liu",
             role = c("aut", "cre"),
             email = "LiuWeideng@gmail.com"),
      person(given = "Jiakun",
             family = "Jiang",
             role = "aut"),
      person(given = "Dewei",
             family = "Xiang",
             role = "aut"),
      person(given = "Xuancheng",
             family = "Zhou",
             role = "aut"))
Author: Wei Liu [aut, cre], Jiakun Jiang [aut], Dewei Xiang [aut],
        Xuancheng Zhou [aut]
Maintainer: Wei Liu <LiuWeideng@gmail.com>
Description: Covariate-augumented generalized factor model is designed
        to account for cross-modal heterogeneity, capture nonlinear
        dependencies among the data, incorporate additional
        information, and provide excellent interpretability while
        maintaining high computational efficiency.
BugReports: https://github.com/feiyoung/CMGFM/issues
License: GPL-3
Depends: irlba, R (>= 3.5.0)
Imports: MASS, stats, GFM, Rcpp (>= 1.0.10)
Suggests: knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.3.1
Repository: https://feiyoung.r-universe.dev
Date/Publication: 2024-06-24 00:59:07 UTC
RemoteUrl: https://github.com/feiyoung/cmgfm
RemoteRef: HEAD
RemoteSha: 874b4c8adc824e65e4eed04557acde2ac74942b3
NeedsCompilation: yes
Packaged: 2026-06-16 08:56:50 UTC; root