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Gaussian Mixture Topic Models

0packages depend
644downloads / year
–test coverage
13/13flavors OK

Overview

About

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.

Changes in 0.2.0
  • Add probability() to extract topic likelihood of documents.
  • Add seeds to textmodel_kmeans() and textmodel_gmm() to initialize clustering with user-provided centers.
  • Add as.seedwords() to create a seed words matrix from **quanteda** dictionaries.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 5.2 min · r-devel-windows-x86_64
Status changes
  • OK13 OKNow
  • OK7 OK2026-09-16
Advisories

none known

Documentation

In release 0.2.0
READMENoVignettesNoNEWSYes · 100% structured · mentions 0.2.0Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
8 (2 internal)
Examples that run
100%3 run in a plain check
Exported functions with examples
43%
Documented parameters
100%
Return-value docs
71%
Help pages citing references
0%

Downloads

644
CRAN downloads in the past year
Rank #20,537 · ~2/day · ~54/mo
Daily download trend is not available in this view yet.
52130 days
64490 days
6441 year
Compare downloads with other packages →
Also on26 r2u1 autocran

Dependencies

Declared dependencies
12 external dependencies (excludes base and recommended)

Installing GMTM adds 21 packages (17 with compiled code, 31 MB of source tarballs). Heaviest: stringi 11 MB, quanteda 4.2 MB, wordvector 4.2 MB.

Depends (1)
R >= 3.5.0
LinkingTo (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (3)
Author, Maintainer since 0.1.0 (2026), Copyright holder
Contributor, Copyright holder · added in 0.2.0
C++ code for GMM and k-means
Contributor, Copyright holder · added in 0.2.0
C++ code for GMM and k-means
Releases (2)

Pick two releases to compare their code metrics.

  • 0.2.0Latest
    record
    2026-09-22 · current release · diff ↗ ·
    added 3 exports
    as.seedwords, group_matrix, probability
  • 0.1.0
    record
    2026-09-15
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-09-15
Total releases
2 / 1 yrs
License
Apache License (>= 2.0)
Minimum R
≥ 3.5.0
Download size
18 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("GMTM")
Watanabe, K., Conrad, S., & Ryan, C. (2026). GMTM: Gaussian Mixture Topic Models (Version 0.2.0) [Computer software]. https://doi.org/10.32614/CRAN.package.GMTM

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for GMTM version 0.2.0 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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