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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