GDAtools2.3 package

Geometric Data Analysis

ahc.plots

Plots for Ascending Hierarchical Clustering

angles.csa

Cosine similarities and angles between CSA and MCA

barplot_contrib

Bar plot of contributions

bcMCA

Between-class MCA

bcPCA

Between-class Principal Component Analysis

bootvalid_supvars

Bootstrap validation (supplementary variables)

bootvalid_variables

Bootstrap validation (active variables)

break_interaction

Additive Breakdowns of Variances

burt

Burt table

coiMCA

Coinertia analysis between two groups of categorical variables

coiPCA

Coinertia analysis between two groups of numerical variables

conc.ellipse

Concentration ellipses

contrib

Contributions of active variables

csMCA

Class Specific Analysis

DA

Discriminant Analysis

DAQ

Discriminant Analysis of Qualitative Variables

deprecated

Deprecated functions

dichotom

Dichotomizes the variables in a data frame

dichotomixed

Dichotomizes the factor variables in a mixed format data frame

dimcontrib

Description of the contributions to axes

dimdescr

Description of the dimensions

dimeta2

Correlation ratios (aka eta-squared) of supplementary variables

dimtypicality

Typicality tests for supplementary variables

dist.chi2

Chi-squared distance

flip.mca

Flips the coordinates

getindexcat

Names of the categories in a data frame

ggadd_attractions

Plot of attractions between categories

ggadd_chulls

Convex hulls for a categorical supplementary variable

ggadd_corr

Heatmap of under/over-representation of a supplementary variable

ggadd_density

Density plot of a supplementary variable

ggadd_ellipses

Confidence ellipses

ggadd_interaction

Plot of interactions between two categorical supplementary variables

ggadd_kellipses

Concentration ellipses and k-inertia ellipses

ggadd_partial

Main and partial effect of a supplementary variable

ggadd_supind

Plot of supplementary individuals

ggadd_supvar

Plot of a categorical supplementary variable

ggadd_supvars

Plot of categorical supplementary variables

ggaxis_variables

Plot of variables on a single axis

ggbootvalid_supvars

Ellipses of bootstrap validation (supplementary variables)

ggbootvalid_variables

Ellipses of bootstrap validation (active variables)

ggcloud_indiv

Plot of the cloud of individuals

ggcloud_variables

Plot of the cloud of variables

ggeta2_variables

eta-squared plot

ggsmoothed_supvar

Plots the density a supplementary variable

gPCA

Generalized Principal Component Analysis

homog.test

Homogeneity test for a categorical supplementary variable

ijunk

App for junk categories of specific MCA

MCAiv

Multiple Correspondence Analysis with Instrumental Variables

MCAoiv

Multiple Correspondence Analysis with Orthogonal Instrumental Variable...

medoids

Medoids of clusters

modif.rate

Benzecri's modified rates of variance

multiMCA

Multiple Factor Analysis

nsca.biplot

Biplot for Nonsymmetric Correspondence Analysis

nsCA

Nonsymmetric Correspondence Analysis

PCAiv

Principal Component Analysis with Instrumental Variables

PCAoiv

Principal Component Analysis with Orthogonal Instrumental Variables

planecontrib

Contributions to a plane

plot.csMCA

Plot of class specific MCA

plot.multiMCA

Plot of Multiple Factor Analysis

plot.speMCA

Plot of specific MCA

plot.stMCA

Plot of standardized MCA

quadrant

Quadrant of active individuals

quasindep

Quasi-correspondence analysis

reshape_between

Reshapes objects created with bcMCA()

rvcoef

RV coefficient

scaled.dev

Scaled deviations for a categorical supplementary variable

speMCA

specific MCA

stMCA

Standardized MCA

supind

Statistics for supplementary individuals

supvar

Statistics for a categorical supplementary variable

supvars

Statistics for categorical supplementary variables

tabcontrib

Table with the main contributions of categories to an axis

textindsup

Plot of supplementary individuals

textvarsup

Plot of a categorical supplementary variable

translate.logit

Deprecated function

wcMCA

Within-class MCA

wcPCA

Within-class Principal Component Analysis

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.).

  • Maintainer: Nicolas Robette
  • License: GPL (>= 2)
  • Last published: 2025-05-29