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: |
1.1.3 |
| Depends: |
R (≥ 2.10) |
| Imports: |
matrixStats, splines, slam, lda, stringr, Matrix, glmnet, Rcpp (≥ 0.11.3), grDevices, graphics, stats, utils |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
igraph, SnowballC, tm (≥ 0.6), huge, clue, wordcloud, KernSmooth, NLP, LDAvis, geometry, Rtsne |
| Published: |
2016-01-15 |
| Author: |
Margaret E. Roberts, Brandon M. Stewart and Dustin Tingley |
| Maintainer: |
Brandon Stewart <bms4 at princeton.edu> |
| License: |
MIT + file LICENSE |
| URL: |
http://structuraltopicmodel.com |
| NeedsCompilation: |
yes |
| Citation: |
stm citation info |
| Materials: |
NEWS |
| CRAN checks: |
stm results |