stm: 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.

Version: 1.2.2
Depends: R (≥ 2.10)
Imports: matrixStats, splines, slam, lda, quanteda, stringr, Matrix, glmnet, Rcpp (≥ 0.11.3), grDevices, graphics, stats, utils, data.table, quadprog
LinkingTo: Rcpp, RcppArmadillo
Suggests: igraph, SnowballC, tm (≥ 0.6), huge, clue, wordcloud, KernSmooth, NLP, LDAvis, geometry, Rtsne, testthat
Published: 2017-03-28
Author: Margaret Roberts [aut, cre], Brandon Stewart [aut, cre], Dustin Tingley [aut, cre], Kenneth Benoit [ctb]
Maintainer: Brandon Stewart <bms4 at princeton.edu>
BugReports: https://github.com/bstewart/stm/issues
License: MIT + file LICENSE
URL: http://structuraltopicmodel.com
NeedsCompilation: yes
Citation: stm citation info
Materials: NEWS
CRAN checks: stm results

Downloads:

Reference manual: stm.pdf
Vignettes: Using stm
Package source: stm_1.2.2.tar.gz
Windows binaries: r-devel: stm_1.2.2.zip, r-release: stm_1.2.2.zip, r-oldrel: stm_1.2.2.zip
OS X El Capitan binaries: r-release: stm_1.2.2.tgz
OS X Mavericks binaries: r-oldrel: stm_1.2.2.tgz
Old sources: stm archive

Reverse dependencies:

Reverse depends: stmgui
Reverse imports: stmBrowser, stmCorrViz, themetagenomics

Linking:

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