doi:10.1007/1-4020-2236-0>), such as MCA variants (Specific Multiple Correspondence Analysis, Class Specific Analysis), many graphical and statistical aids to interpretation (structuring factors, concentration ellipses, inductive tests, bootstrap validation, etc.) and multiple-table analysis (Multiple Factor Analysis, between- and inter-class analysis, Principal Component Analysis and Correspondence Analysis with Instrumental Variables, etc.).">

GDAtools: Geometric Data Analysis (original) (raw)

Many tools for Geometric Data Analysis (Le Roux & Rouanet (2005) <doi:10.1007/1-4020-2236-0>), such as MCA variants (Specific Multiple Correspondence Analysis, Class Specific Analysis), many graphical and statistical aids to interpretation (structuring factors, concentration ellipses, inductive tests, bootstrap validation, etc.) and multiple-table analysis (Multiple Factor Analysis, between- and inter-class analysis, Principal Component Analysis and Correspondence Analysis with Instrumental Variables, etc.).

Version: 2.1
Imports: descriptio (≥ 1.2), FactoMineR, ggplot2, ggrepel, rlang
Suggests: R.rsp, rmarkdown, knitr, rmdformats, TraMineR, sf, shiny, miniUI, esquisse, rclipboard, factoextra, ade4
Published: 2024-03-07
DOI: 10.32614/CRAN.package.GDAtools
Author: Nicolas Robette [aut, cre]
Maintainer: Nicolas Robette <nicolas.robette at uvsq.fr>
BugReports: https://github.com/nicolas-robette/GDAtools/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/nicolas-robette/GDAtools,https://nicolas-robette.github.io/GDAtools/
NeedsCompilation: no
Citation: GDAtools citation info
Materials: README NEWS
CRAN checks: GDAtools results

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