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) <doi:10.1111/ajps.12103> and Roberts et. al. (2016) <doi:10.1080/01621459.2016.1141684>. Vignette is Roberts et. al. (2019) <doi:10.18637/jss.v091.i02>.
Version: | 1.3.7 |
Depends: | R (≥ 3.5.0), methods |
Imports: | Rcpp (≥ 0.11.3), data.table, glmnet, grDevices, graphics, lda, Matrix, matrixStats, parallel, quadprog, quanteda, slam, splines, stats, stringr, utils |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | clue, geometry, huge, igraph, LDAvis, KernSmooth, NLP, rsvd, Rtsne, SnowballC, spelling, testthat, tm (≥ 0.6), wordcloud |
Published: | 2023-12-01 |
DOI: | 10.32614/CRAN.package.stm |
Author: | Margaret Roberts [aut], Brandon Stewart [aut, cre], Dustin Tingley [aut], Kenneth Benoit [ctb] |
Maintainer: | Brandon Stewart <bms4 at princeton.edu> |
BugReports: | https://github.com/bstewart/stm/issues |
License: | MIT + file LICENSE |
URL: | http://www.structuraltopicmodel.com/ |
NeedsCompilation: | yes |
Language: | en-US |
Citation: | stm citation info |
Materials: | NEWS |
In views: | NaturalLanguageProcessing |
CRAN checks: | stm results |
Reference manual: | stm.pdf |
Vignettes: |
Using stm |
Package source: | stm_1.3.7.tar.gz |
Windows binaries: | r-devel: stm_1.3.7.zip, r-release: stm_1.3.7.zip, r-oldrel: stm_1.3.7.zip |
macOS binaries: | r-release (arm64): stm_1.3.7.tgz, r-oldrel (arm64): stm_1.3.7.tgz, r-release (x86_64): stm_1.3.7.tgz, r-oldrel (x86_64): stm_1.3.7.tgz |
Old sources: | stm archive |
Reverse depends: | stmgui |
Reverse imports: | discursive, stmCorrViz, stminsights, sts, Twitmo |
Reverse suggests: | oolong, sentopics, tidytext, topicdoc |
Reverse enhances: | quanteda |
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