Gaussian mixture models (GMM) and k-means for topic analysis of dense document vectors. The underlying clustering functions rely on the Armadillo library (Sanderson & Curtin, 2017) <doi:10.1109/ICSPCS.2017.8270510>.
| Version: |
0.2.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
quanteda (≥ 4.0.0), proxyC, wordvector (≥ 0.6.4), Rcpp, RcppArmadillo |
| LinkingTo: |
Rcpp, RcppArmadillo (≥ 0.7.600.1.0) |
| Suggests: |
testthat, spelling, rmarkdown, knitr, withr |
| Published: |
2026-09-22 |
| DOI: |
10.32614/CRAN.package.GMTM |
| Author: |
Kohei Watanabe 
[aut, cre, cph],
Sanderson Conrad [ctb, cph] (C++ code for GMM and k-means),
Curtin Ryan [ctb, cph] (C++ code for GMM and k-means) |
| Maintainer: |
Kohei Watanabe <watanabe.kohei at gmail.com> |
| License: |
Apache License (≥ 2.0) |
| NeedsCompilation: |
yes |
| Language: |
en-US |
| Materials: |
NEWS |
| CRAN checks: |
GMTM results |