lda: Collapsed Gibbs sampling methods for topic models

This package 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 writtten 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: 1.3.1
Depends: R (≥ 2.10)
Suggests: Matrix, ggplot2, penalized
Published: 2011-11-03
Author: Jonathan Chang
Maintainer: Jonathan Chang <jonchang@fb.com>, Andrew Dai <a.dai at ed.ac.uk>
License: LGPL
CRAN checks: lda results

Downloads:

Package source: lda_1.3.1.tar.gz
MacOS X binary: lda_1.3.1.tgz
Windows binary: lda_1.3.1.zip
Reference manual: lda.pdf
Old sources: lda archive

Reverse dependencies:

Reverse suggests: topicmodels