DESCRIPTION

Package: stm
Title: Estimation of the Structural Topic Model
Version: 1.3.7
Authors@R: c(
    person("Margaret", "Roberts", email="meroberts@ucsd.edu", role="aut"),
    person("Brandon", "Stewart", email="bms4@princeton.edu", role=c("aut","cre")),
    person("Dustin", "Tingley", email="dtingley@gov.harvard.edu", role="aut"),
    person("Kenneth","Benoit", email="kbenoit@lse.ac.uk", role="ctb"))
Description: 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>.
Depends: 
  R (>= 3.5.0), 
  methods
LinkingTo: Rcpp, RcppArmadillo
Imports: 
  Rcpp (>= 0.11.3),
  data.table,
  glmnet,
  grDevices,
  graphics,
  lda,
  Matrix,
  matrixStats,
  parallel,
  quadprog,
  quanteda,
  slam,
  splines,
  stats,
  stringr,
  utils
Suggests: 
  clue,
  geometry,
  huge,
  igraph,
  LDAvis,
  KernSmooth,
  NLP,
  rsvd,
  Rtsne,
  SnowballC,
  spelling,
  testthat,
  tm (>= 0.6),
  wordcloud
Encoding: UTF-8
LazyData: yes
License: MIT + file LICENSE
URL: http://www.structuraltopicmodel.com/
BugReports: https://github.com/bstewart/stm/issues
RoxygenNote: 7.2.3
Language: en-US