Package: mlstm
Type: Package
Title: Multilevel Supervised Topic Models with Multiple Outcomes
Version: 0.1.7
Authors@R: 
    person("Tomoya", "Himeno", email = "bd24f002@g.hit-u.ac.jp", role = c("aut", "cre"))
Description: Fits latent Dirichlet allocation (LDA), supervised topic models,
    and multilevel supervised topic models for text data with multiple
    outcome variables. Core estimation routines are implemented in C++
    using the 'Rcpp' ecosystem. 
    For topic models, see Blei et al. (2003) <https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf>.
    For supervised topic models, see Blei and McAuliffe (2007) <https://papers.nips.cc/paper_files/paper/2007/hash/d56b9fc4b0f1be8871f5e1c40c0067e7-Abstract.html>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: Rcpp, Matrix, data.table, RcppParallel, stats
LinkingTo: Rcpp, RcppArmadillo, RcppParallel, BH
SystemRequirements: C++17
RoxygenNote: 7.3.3
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Config/testthat/edition: 3
URL: https://thimeno1993.github.io/mlstm/
BugReports: https://github.com/thimeno1993/mlstm/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-04-14 12:52:31 UTC; tomoya
Author: Tomoya Himeno [aut, cre]
Maintainer: Tomoya Himeno <bd24f002@g.hit-u.ac.jp>
Repository: CRAN
Date/Publication: 2026-04-14 13:30:02 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2026-04-23 02:15:02 UTC; windows
Archs: x64
