mlstm: Multilevel Supervised Topic Models with Multiple Outcomes

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>.

Version:	0.1.6
Depends:	R (≥ 4.0.0)
Imports:	Rcpp, Matrix, data.table, RcppParallel, stats
LinkingTo:	Rcpp, RcppArmadillo, RcppParallel, BH
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-04-03
DOI:	10.32614/CRAN.package.mlstm (may not be active yet)
Author:	Tomoya Himeno [aut, cre]
Maintainer:	Tomoya Himeno <bd24f002 at g.hit-u.ac.jp>
BugReports:	https://github.com/thimeno1993/mlstm/issues
License:	MIT + file LICENSE
URL:	https://thimeno1993.github.io/mlstm/
NeedsCompilation:	yes
SystemRequirements:	C++17
Materials:	README, NEWS
CRAN checks:	mlstm results

Documentation:

Reference manual:	mlstm.html , mlstm.pdf
Vignettes:	Introduction to mlstm (source, R code)

Downloads:

Package source:	mlstm_0.1.6.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): mlstm_0.1.6.tgz, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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