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.


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install.packages("lda")

1.4.2 by Jonathan Chang, 2 years ago


Browse source code at https://github.com/cran/lda


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