Package: mccca 1.1.0.1

Mariko Takagishi

mccca: Visualizing Class Specific Heterogeneous Tendencies in Categorical Data

Performing multiple-class cluster correspondence analysis(MCCCA). The main functions are create.MCCCAdata() to create a list to be applied to MCCCA, MCCCA() to apply MCCCA, and plot.mccca() for visualizing MCCCA result. Methods used in the package refers to Mariko Takagishi and Michel van de Velden (2022)<doi:10.1080/10618600.2022.2035737>.

Authors:Mariko Takagishi [aut, cre]

mccca_1.1.0.1.tar.gz
mccca_1.1.0.1.tar.gz(r-4.7-arm64)mccca_1.1.0.1.tar.gz(r-4.7-x86_64)mccca_1.1.0.1.tar.gz(r-4.6-arm64)mccca_1.1.0.1.tar.gz(r-4.6-x86_64)
mccca_1.1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mccca/json (API)

# Install 'mccca' in R:
install.packages('mccca', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

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

openblascppopenmp

1.00 score 185 downloads 7 exports 25 dependencies

Last updated from:b5b9a3463f. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK152
linux-devel-x86_64OK134
source / vignettesOK192
linux-release-arm64OK158
linux-release-x86_64OK152
wasm-releaseOK134

Exports:create.MCCCAdatacreate.propgenerate.cate.listgenerate.cateclsgenerate.extgenerate.onedataMCCCA

Dependencies:abindclicpp11farverggplot2gluegtableisobandlabelinglifecyclemagicmagrittrR6RColorBrewerRcppRcppArmadillorlangS7scalesstringistringrvctrsviridisLitewithrwordcloud