Fast Topic Models Using Varimax R package tmfast version 0.1.1 Fits topic models using varimax-rotated principal component analysis (PCA), following the "vintage factor analysis" approach of Rohe & Zheng (2020) <doi:10.48550/arXiv.2004.05387>. Leverages truncated PCA via 'irlba' for sparse matrices, enabling fast model fitting on large corpora. Includes an information-theoretic approach to vocabulary selection, 'broom'-compatible tidiers for extracting word-topic and topic-document matrices into a tidy data workflow, and samplers for constructing simulated corpora for benchmarking and method evaluation. Software Depends: R (>= 4.1.0) Imports: assertthat, purrr, dplyr, tidyr, magrittr, rlang, stringr, tibble, tidyselect, irlba, tidytext, glue, Matrix, generics, psych, cli Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ggbeeswarm, ggplot2, Rtsne, umap, lpSolve, janeaustenr, stm, tictoc, furrr, reshape2, tmfast.realbooks D. Hicks <hicks.daniel.j@gmail.com> Comprehensive R Archive Network (CRAN) D. Hicks [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-7945-4416>) GPL (>= 3) 2026-05-30 application/tgz https://CRAN.R-project.org/package=tmfast doi:10.32614/CRAN.package.tmfast