Package: MCAtools 1.0.0
MCAtools: Multiple Correspondence Analysis Toolkit (Phi-Divergence Framework)
A toolkit for performing Multiple Correspondence Analysis (MCA) based on the phi-divergence framework of Cressie and Read (1984) <doi:10.1111/j.2517-6161.1984.tb01318.x>. Provides implementations for MCA computation mca_analysis(), visualization plot_mca(), and symbolic equation generation generate_mca_equation(), designed for interpretability, flexibility, and analytical consistency with generalized divergence measures.
Authors:
MCAtools_1.0.0.tar.gz
MCAtools_1.0.0.zip(r-4.7-any)MCAtools_1.0.0.zip(r-4.6-any)MCAtools_1.0.0.zip(r-4.5-any)
MCAtools_1.0.0.tgz(r-4.6-any)MCAtools_1.0.0.tgz(r-4.5-any)
MCAtools_1.0.0.tar.gz(r-4.7-any)MCAtools_1.0.0.tar.gz(r-4.6-any)
MCAtools_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MCAtools/json (API)
| # Install 'MCAtools' in R: |
| install.packages('MCAtools', repos = c('https://nskamdem.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/nskamdem/mcatools/issues
- electricity_africa - Electricity market structures and electricity supply costs in Sub-Saharan Africa
Last updated from:52f521e329. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 122 | ||
| source / vignettes | OK | 169 | ||
| linux-release | OK | 118 | ||
| macos-release | OK | 181 | ||
| macos-oldrel | OK | 172 | ||
| windows-devel | OK | 76 | ||
| windows-release | OK | 53 | ||
| windows-oldrel | OK | 64 | ||
| wasm-release | OK | 104 |
Exports:generate_mca_equationmca_analysisplot_mca
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Electricity market structures and electricity supply costs in Sub-Saharan Africa | electricity_africa |
| Extract a Symbolic Equation for an MCA Dimension | generate_mca_equation |
| Multiple Correspondence Analysis with lambda-divergence and supplementary qualitative variables | mca_analysis |
| Plot Multiple Correspondence Analysis Results | plot_mca |