stm (1.3.5)

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Estimation of the Structural Topic Model.

The Structural Topic Model (STM) allows researchers to estimate topic models with document-level covariates. The package also includes tools for model selection, visualization, and estimation of topic-covariate regressions. Methods developed in Roberts et al (2014) and Roberts et al (2016) . Vignette is Roberts et al (2019) .

Maintainer: Brandon Stewart
Author(s): Margaret Roberts [aut], Brandon Stewart [aut, cre], Dustin Tingley [aut], Kenneth Benoit [ctb]

License: MIT + file LICENSE

Uses: data.table, glmnet, lda, Matrix, matrixStats, quadprog, quanteda, Rcpp, slam, stringr, KernSmooth, clue, geometry, igraph, tm, testthat, huge, wordcloud, SnowballC, NLP, Rtsne, LDAvis, rsvd, spelling
Reverse depends: stmgui
Reverse suggests: chorrrds, quanteda, tidytext

Released 5 months ago.

8 previous versions



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Related packages: corpora, gsubfn, kernlab, languageR, lsa, tm, wordnet, zipfR, RWeka, RKEA, openNLP, skmeans, tau, tm.plugin.mail, lda, textcat, topicmodels, tm.plugin.dc, textir, movMF(20 best matches, based on common tags.)

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