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mlstm  

Multilevel Supervised Topic Models with Multiple Outcomes
View on CRAN: Click here


Download and install mlstm package within the R console
Install from CRAN:
install.packages("mlstm")

Install from Github:
library("remotes")
install_github("cran/mlstm")

Install by package version:
library("remotes")
install_version("mlstm", "0.1.6")



Attach the package and use:
library("mlstm")
Maintained by
Tomoya Himeno
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-19
Latest Update: 2026-04-19
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>.
How to cite:
Tomoya Himeno (2026). mlstm: Multilevel Supervised Topic Models with Multiple Outcomes. R package version 0.1.6, https://cran.r-project.org/web/packages/mlstm. Accessed 17 Jul. 2026.
Previous versions and publish date:
(2026-07-09 06:31), 0.1.6 (2026-04-03 11:00)
Other packages that cited mlstm R package
View mlstm citation profile
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Complete documentation for mlstm
Functions, R codes and Examples using the mlstm R package
Full mlstm package functions and examples
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