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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>.
Version: | 1.1.0.1 |
Depends: | R (≥ 4.1.0) |
Imports: | magic, stringr, ggplot2, wordcloud, RColorBrewer, stats, utils, grDevices, Rcpp (≥ 1.0.9) |
LinkingTo: | Rcpp, RcppArmadillo |
Published: | 2024-01-24 |
DOI: | 10.32614/CRAN.package.mccca |
Author: | Mariko Takagishi [aut, cre] |
Maintainer: | Mariko Takagishi <m.takagishi0728 at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
CRAN checks: | mccca results |
Reference manual: | mccca.pdf |
Package source: | mccca_1.1.0.1.tar.gz |
Windows binaries: | r-devel: mccca_1.1.0.1.zip, r-release: mccca_1.1.0.1.zip, r-oldrel: mccca_1.1.0.1.zip |
macOS binaries: | r-release (arm64): mccca_1.1.0.1.tgz, r-oldrel (arm64): mccca_1.1.0.1.tgz, r-release (x86_64): mccca_1.1.0.1.tgz, r-oldrel (x86_64): mccca_1.1.0.1.tgz |
Old sources: | mccca archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.