maptpx: MAP Estimation of Topic Models

Maximum a posteriori (MAP) estimation for topic models (i.e., Latent Dirichlet Allocation) in text analysis, as described in Taddy (2012) 'On estimation and selection for topic models'. Previous versions of this code were included as part of the 'textir' package. If you want to take advantage of openmp parallelization, uncomment the relevant flags in src/MAKEVARS before compiling.

Version: 1.9-7
Depends: R (≥ 2.10), slam
Suggests: MASS
Published: 2020-05-28
Author: Matt Taddy
Maintainer: Matt Taddy <mataddy at gmail.com>
License: GPL-3
URL: http://taddylab.com
NeedsCompilation: yes
Citation: maptpx citation info
CRAN checks: maptpx results

Documentation:

Reference manual: maptpx.pdf

Downloads:

Package source: maptpx_1.9-7.tar.gz
Windows binaries: r-devel: maptpx_1.9-7.zip, r-devel-UCRT: maptpx_1.9-7.zip, r-release: maptpx_1.9-7.zip, r-oldrel: maptpx_1.9-7.zip
macOS binaries: r-release (arm64): maptpx_1.9-7.tgz, r-release (x86_64): maptpx_1.9-7.tgz, r-oldrel: maptpx_1.9-7.tgz
Old sources: maptpx archive

Reverse dependencies:

Reverse imports: cellTree, CountClust

Linking:

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