Package: maptpx 1.9-7
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
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maptpx.pdf |maptpx.html✨
maptpx/json (API)
# Install 'maptpx' in R: |
install.packages('maptpx', repos = c('https://taddylab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/taddylab/maptpx/issues
Last updated 4 years agofrom:a6639c25ff. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 04 2024 |
R-4.5-win-x86_64 | OK | Nov 04 2024 |
R-4.5-linux-x86_64 | OK | Nov 04 2024 |
R-4.4-win-x86_64 | OK | Nov 04 2024 |
R-4.4-mac-x86_64 | OK | Nov 04 2024 |
R-4.4-mac-aarch64 | OK | Nov 04 2024 |
R-4.3-win-x86_64 | OK | Nov 04 2024 |
R-4.3-mac-x86_64 | OK | Nov 04 2024 |
R-4.3-mac-aarch64 | OK | Nov 04 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 |