Package: maptpx 1.9-7

Matt Taddy

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.

Authors:Matt Taddy <[email protected]>

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maptpx.pdf |maptpx.html
maptpx/json (API)

# Install 'maptpx' in R:
install.packages('maptpx', repos = c('https://taddylab.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/taddylab/maptpx/issues

Uses libs:
  • openblas– Optimized BLAS

On CRAN:

map-estimationtopic-modelingopenblas

6.27 score 19 stars 2 packages 326 scripts 360 downloads 1 mentions 8 exports 1 dependencies

Last updated 5 years agofrom:a6639c25ff. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 03 2025
R-4.5-win-x86_64OKJan 03 2025
R-4.5-linux-x86_64OKJan 03 2025
R-4.4-win-x86_64OKJan 03 2025
R-4.4-mac-x86_64OKJan 03 2025
R-4.4-mac-aarch64OKJan 03 2025
R-4.3-win-x86_64OKJan 03 2025
R-4.3-mac-x86_64OKJan 03 2025
R-4.3-mac-aarch64OKJan 03 2025

Exports:expitlogitnormalizepredict.topicsrdirstm_tfidftopicstopicVar

Dependencies:slam