Implements latent Dirichlet allocation (LDA) and related models. This includes (but is not limited to) sLDA, corrLDA, and the mixed-membership stochastic blockmodel. Inference for all of these models is implemented via a fast collapsed Gibbs sampler written in C. Utility functions for reading/writing data typically used in topic models, as well as tools for examining posterior distributions are also included.
| Version: | 1.5.2 | 
| Depends: | R (≥ 4.3.0) | 
| Imports: | methods (≥ 4.3.0) | 
| Suggests: | Matrix, reshape2, ggplot2 (≥ 3.4.4), penalized, nnet | 
| Published: | 2024-04-27 | 
| DOI: | 10.32614/CRAN.package.lda | 
| Author: | Jonathan Chang | 
| Maintainer: | Santiago Olivella <olivella at unc.edu> | 
| License: | LGPL-2.1 | LGPL-3 [expanded from: LGPL (≥ 2.1)] | 
| NeedsCompilation: | yes | 
| Materials: | README | 
| In views: | NaturalLanguageProcessing | 
| CRAN checks: | lda results | 
| Reference manual: | lda.html , lda.pdf | 
| Package source: | lda_1.5.2.tar.gz | 
| Windows binaries: | r-devel: lda_1.5.2.zip, r-release: lda_1.5.2.zip, r-oldrel: lda_1.5.2.zip | 
| macOS binaries: | r-release (arm64): lda_1.5.2.tgz, r-oldrel (arm64): lda_1.5.2.tgz, r-release (x86_64): lda_1.5.2.tgz, r-oldrel (x86_64): lda_1.5.2.tgz | 
| Old sources: | lda archive | 
| Reverse imports: | ldaPrototype, NetMix, stm, tosca | 
| Reverse suggests: | LDAvis, qdap, sentopics, textmineR, topicmodels | 
| Reverse enhances: | quanteda | 
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