lda
Collapsed Gibbs Sampling Methods for Topic Models
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.5.2 |
rolling linux/jammy R-4.5 | lda_1.5.2.tar.gz |
3.7 MiB |
1.5.2 |
rolling linux/noble R-4.5 | lda_1.5.2.tar.gz |
3.7 MiB |
1.5.2 |
rolling source/ R- | lda_1.5.2.tar.gz |
3.6 MiB |
1.5.2 |
latest linux/jammy R-4.5 | lda_1.5.2.tar.gz |
3.7 MiB |
1.5.2 |
latest linux/noble R-4.5 | lda_1.5.2.tar.gz |
3.7 MiB |
1.5.2 |
latest source/ R- | lda_1.5.2.tar.gz |
3.6 MiB |
1.5.2 |
2026-04-26 source/ R- | lda_1.5.2.tar.gz |
3.6 MiB |
1.5.2 |
2026-04-23 source/ R- | lda_1.5.2.tar.gz |
3.6 MiB |
1.5.2 |
2026-04-09 windows/windows R-4.5 | lda_1.5.2.zip |
3.7 MiB |
1.5.2 |
2025-04-20 source/ R- | lda_1.5.2.tar.gz |
3.6 MiB |