Package: maptpx 1.9-7
Matt Taddy
maptpx: MAP Estimation of Topic Models
Maximum a posteriori (MAP) estimation for topic models (i.e., Latent Dirichlet Allocation) in text analysis, as described in Taddy (2012) 'On estimation and selection for topic models'. Previous versions of this code were included as part of the 'textir' package. If you want to take advantage of openmp parallelization, uncomment the relevant flags in src/MAKEVARS before compiling.
Authors:
maptpx_1.9-7.tar.gz
maptpx_1.9-7.tar.gz(r-4.5-noble)maptpx_1.9-7.tar.gz(r-4.4-noble)
maptpx_1.9-7.tgz(r-4.4-emscripten)maptpx_1.9-7.tgz(r-4.3-emscripten)
maptpx.pdf |maptpx.html✨
maptpx/json (API)
| # Install 'maptpx' in R: |
| install.packages('maptpx', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:a8d05d00d9. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 27 2024 |
| R-4.5-linux-x86_64 | OK | Dec 27 2024 |
Exports:expitlogitnormalizepredict.topicsrdirstm_tfidftopicstopicVar
Dependencies:slam
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Utilities for count matrices | normalize stm_tfidf |
| topic predict | predict.topics |
| Dirichlet RNG | rdir |
| Estimation for Topic Models | topics |
| topic variance | expit logit topicVar |
