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.
Documentation:
Downloads:
Reverse dependencies:
| Reverse imports: |
ergmclust, ldaPrototype, NetMix, stm, tosca |
| Reverse suggests: |
LDAvis, psychtm, qdap, quanteda, sentopics, textmineR, topicmodels |
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