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-4.5-noble)mccca_1.1.0.1.tar.gz(r-4.4-noble)
mccca_1.1.0.1.tgz(r-4.4-emscripten)mccca_1.1.0.1.tgz(r-4.3-emscripten)
mccca.pdf |mccca.html✨
mccca/json (API)

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

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

openblascppopenmp

1.00 score 199 downloads 7 exports 35 dependencies

Last updated 1 years agofrom:b5b9a3463f. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 19 2025
R-4.5-linux-x86_64OKJan 19 2025

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

Dependencies:abindclicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagicmagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalesstringistringrtibbleutf8vctrsviridisLitewithrwordcloud