Package: stm
Type: Package
Title: Estimation of the Structural Topic Model
Version: 1.3.3
Date: 2018-1-26
Author: Margaret Roberts [aut, cre], 
        Brandon Stewart [aut, cre],
        Dustin Tingley [aut, cre],
        Kenneth Benoit [ctb]
Maintainer: Brandon Stewart <bms4@princeton.edu>
Depends: R (>= 3.2.2)
LinkingTo: Rcpp, RcppArmadillo
Imports: matrixStats, splines, slam, lda, quanteda, stringr, Matrix,
        glmnet, Rcpp (>= 0.11.3), grDevices, graphics, stats, utils,
        data.table, quadprog, parallel, methods
Suggests: igraph, SnowballC, tm (>= 0.6), huge, clue, wordcloud,
        KernSmooth, NLP, LDAvis, geometry, Rtsne, testthat, rsvd
LazyData: yes
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>.
License: MIT + file LICENSE
URL: http://structuraltopicmodel.com
BugReports: https://github.com/bstewart/stm/issues
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-01-28 18:42:14 UTC; bms4
Repository: CRAN
Date/Publication: 2018-01-28 21:13:01 UTC
Built: R 3.5.2; x86_64-w64-mingw32; 2019-01-30 21:19:00 UTC; windows
Archs: i386, x64
