GFM: Generalized Factor Model

Generalized factor model is implemented for ultra-high dimensional data with mixed-type variables. Two algorithms, variational EM and alternate maximization, are designed to implement the generalized factor model, respectively. The factor matrix and loading matrix together with the number of factors can be well estimated. This model can be employed in social and behavioral sciences, economy and finance, and genomics, to extract interpretable nonlinear factors. More details can be referred to Wei Liu, Huazhen Lin, Shurong Zheng and Jin Liu. (2021) <doi:10.1080/01621459.2021.1999818>.

Version: 1.2.1
Depends: doSNOW, parallel, R (≥ 3.5.0)
Imports: MASS, stats, irlba, Rcpp, methods
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2023-08-11
DOI: 10.32614/CRAN.package.GFM
Author: Wei Liu [aut, cre], Huazhen Lin [aut], Shurong Zheng [aut], Jin Liu [aut], Jinyu Nie [aut]
Maintainer: Wei Liu <LiuWeideng at>
License: GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: GFM results


Reference manual: GFM.pdf
Vignettes: GFM: A Simple Transcriptomics Data
GFM: alternate maximization and information criterion


Package source: GFM_1.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): GFM_1.2.1.tgz, r-oldrel (arm64): GFM_1.2.1.tgz, r-release (x86_64): GFM_1.2.1.tgz, r-oldrel (x86_64): GFM_1.2.1.tgz
Old sources: GFM archive

Reverse dependencies:

Reverse imports: CMGFM


Please use the canonical form to link to this page.