Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) when variables are categorical, Multiple Factor Analysis (MFA) when variables are structured in groups.
| Version: | 1.0.0 |
| Depends: | R (≥ 4.1.0) |
| Suggests: | covr,devtools,factoextra,FactoMineR,knitr,renv,testthat |
| Published: | 2025-04-24 |
| DOI: | 10.32614/CRAN.package.booklet |
| Author: | Alex Yahiaoui Martinez |
| Maintainer: | Alex Yahiaoui Martinez <yahiaoui-martinez.alex at outlook.com> |
| BugReports: | https://github.com/alexym1/booklet/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/alexym1/booklet,https://alexym1.github.io/booklet/ |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | booklet results |
| Reference manual: | booklet.html ,booklet.pdf |
| Vignettes: | Comparison with FactoMineR (source,R code) Introduction to booklet (source,R code) Data visualization with factoextra (source,R code) |
| Package source: | booklet_1.0.0.tar.gz |
| Windows binaries: | r-devel:booklet_1.0.0.zip, r-release:booklet_1.0.0.zip, r-oldrel:booklet_1.0.0.zip |
| macOS binaries: | r-release (arm64):booklet_1.0.0.tgz, r-oldrel (arm64):booklet_1.0.0.tgz, r-release (x86_64):booklet_1.0.0.tgz, r-oldrel (x86_64):booklet_1.0.0.tgz |
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