GDAtools: A Toolbox for Geometric Data Analysis and More
Contains functions for 'specific' Multiple Correspondence Analysis,
Class Specific Analysis, Multiple Factor Analysis, 'standardized' MCA, computing and plotting structuring factors and concentration ellipses,
inductive tests and others tools for Geometric Data Analysis (Le Roux & Rouanet (2005) <doi:10.1007/1-4020-2236-0>). It also provides functions
for the translation of logit models coefficients into percentages (Deauvieau (2010) <doi:10.1177/0759106309352586>), weighted contingency tables, an association
measure for contingency tables ("Percentages of Maximum Deviation from Independence", aka PEM, see Cibois (1993) <doi:10.1177/075910639304000103>) and some tools to measure
and plot bivariate associations between variables
(phi, Cramér V, correlation coefficient, eta-squared...).
Version: |
1.7.2 |
Imports: |
MASS, wdm, FactoMineR, nleqslv, nnet, ggplot2, ggrepel, RColorBrewer, rlang, GGally |
Suggests: |
rmarkdown, knitr, rmdformats, cluster, WeightedCluster, vcd, R.rsp |
Published: |
2022-02-22 |
Author: |
Nicolas Robette |
Maintainer: |
Nicolas Robette <nicolas.robette at uvsq.fr> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: |
https://github.com/nicolas-robette/GDAtools,
https://nicolas-robette.github.io/GDAtools/ |
NeedsCompilation: |
no |
Materials: |
README NEWS |
CRAN checks: |
GDAtools results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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