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 gmail.com> BugReports: https://github.com/feiyoung/GFM/issues License: GPL-3 URL: https://github.com/feiyoung/GFM NeedsCompilation: yes Materials: README CRAN checks: GFM results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=GFM to link to this page.
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