Compute maximum likelihood estimators of parameters in a Gaussian factor model using the the matrix-free methodology described in Dai et al. (2020) <doi:10.1080/10618600.2019.1704296>. In contrast to the factanal() function from 'stats' package, fad() can handle high-dimensional datasets where number of variables exceed the sample size and is also substantially faster than the EM algorithms.
| Version: | 0.9-3 |
| Depends: | R (≥ 3.0.2), methods, RSpectra (≥ 0.16-1) |
| Imports: | Matrix (≥ 1.1-0), Rcpp (≥ 0.11.5) |
| LinkingTo: | Rcpp, RSpectra, RcppEigen |
| Suggests: | knitr, GPArotation |
| Published: | 2025-08-27 |
| DOI: | 10.32614/CRAN.package.fad |
| Author: | Somak Dutta [aut, cre], Fan Dai [aut], Ranjan Maitra [ctb] |
| Maintainer: | Somak Dutta <somakd at iastate.edu> |
| BugReports: | https://github.com/somakd/fad/issues |
| License: | GPL-3 |
| URL: | https://github.com/somakd/fad |
| NeedsCompilation: | yes |
| CRAN checks: | fad results |
| Reference manual: | fad.html , fad.pdf |
| Vignettes: |
fad vignette (source, R code) An Introduction to \texttt{FAD} for Exploratory Factor Analysis with High-dimensional Gaussian Data (source, R code) |
| Package source: | fad_0.9-3.tar.gz |
| Windows binaries: | r-devel: fad_0.9-3.zip, r-release: fad_0.9-3.zip, r-oldrel: fad_0.9-3.zip |
| macOS binaries: | r-release (arm64): fad_0.9-3.tgz, r-oldrel (arm64): fad_0.9-3.tgz, r-release (x86_64): fad_0.9-3.tgz, r-oldrel (x86_64): fad_0.9-3.tgz |
| Old sources: | fad archive |
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