Package: poLCAParallel 1.2.7

Sherman Lo

poLCAParallel: Polytomous Variable Latent Class Analysis Parallel

A 'C++' reimplementation of 'poLCA' - latent class analysis and latent class regression models for polytomous outcome variables, also known as latent structure analysis. It attempts to reproduce results and be as similar as possible to the original code, while running faster, especially with multiple repetitions, by utilising multiple threads. Further reading is available on the Queen Mary, University of London, IT Services Research blog <https://blog.hpc.qmul.ac.uk/speeding_up_r_packages/>.

Authors:Sherman Lo [aut, cre], Drew Linzer [aut], Jeffrey Lewis. [aut]

poLCAParallel_1.2.7.tar.gz
poLCAParallel_1.2.7.tar.gz(r-4.7-arm64)poLCAParallel_1.2.7.tar.gz(r-4.7-x86_64)poLCAParallel_1.2.7.tar.gz(r-4.6-arm64)poLCAParallel_1.2.7.tar.gz(r-4.6-x86_64)
poLCAParallel_1.2.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
poLCAParallel/json (API)

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

Bug tracker:https://github.com/qmul/polcaparallel/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • carcinoma - Diagnoses of carcinoma
  • cheating - GPA and chronic cheating
  • election - 2000 National Election Studies survey
  • gss82 - 1982 General Social Survey
  • values - Universalistic vs. particularistic values

On CRAN:

Conda:

openblascpp

2.00 score 362 downloads 11 exports 5 dependencies

Last updated from:fd93a07864. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK265
linux-devel-x86_64OK230
source / vignettesOK288
linux-release-arm64OK241
linux-release-x86_64OK235
wasm-releaseOK202

Exports:blrtpoLCApoLCA.entropypoLCA.posteriorpoLCA.predcellpoLCA.reorderpoLCA.simdatapoLCA.tablepoLCAParallel.goodnessfitpoLCAParallel.sermulti

Dependencies:MASSpoLCARcppRcppArmadilloscatterplot3d