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>.