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mlstm

Multilevel Supervised Topic Models with Multiple Outcomes

v0.1.6 · Apr 3, 2026 · MIT + file LICENSE

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>.

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Dependency Network

Dependencies Reverse dependencies Rcpp Matrix data.table RcppParallel mlstm

Version History

new 0.1.6 Apr 3, 2026