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.


Reference manual

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1.4.2 by Jonathan Chang, 2 years ago

Browse source code at

Authors: Jonathan Chang

Documentation:   PDF Manual  

Task views: Natural Language Processing

LGPL license

Suggests Matrix, reshape2, ggplot2, penalized, nnet

Imported by stm, textmineR, themetagenomics.

Suggested by LDAvis, qdap, quanteda, topicmodels.

See at CRAN