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]>

maptpx_1.9-7.tar.gz
maptpx_1.9-7.tar.gz(r-4.7-arm64)maptpx_1.9-7.tar.gz(r-4.7-x86_64)maptpx_1.9-7.tar.gz(r-4.6-arm64)maptpx_1.9-7.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html
card.svg |card.png
maptpx/json (API)

# Install 'maptpx' in R:
install.packages('maptpx', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas

3.29 score 2 packages 327 scripts 426 downloads 1 mentions 8 exports 1 dependencies

Last updated from:a8d05d00d9. Checks:5 OK, 1 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK141
linux-devel-x86_64OK101
source / vignettesOK166
linux-release-arm64OK136
linux-release-x86_64OK99
wasm-releaseFAIL96

Exports:expitlogitnormalizepredict.topicsrdirstm_tfidftopicstopicVar

Dependencies:slam