Multiple Correspondence Analysis Toolkit (Phi-Divergence Framework)
MCAtools is an R package designed to perform Multiple Correspondence Analysis (MCA) using the φ-divergence framework introduced by Cressie & Read (1984). The package extends traditional MCA by allowing more general divergence measures, improving interpretability and robustness in categorical data analysis.
It provides three main functions:
mca\_analysis() — performs MCA computation under the
φ-divergence framework.plot\_mca() — visualizes individuals and variable
modalities on the selected principal dimensions.generate\_mca\_equation() — produces a symbolic or
algebraic representation of the MCA dimensions for analytical
interpretation.You can install the development version directly from GitHub:
# install.packages("devtools")
devtools::install\_github("nskamdem/MCAtools")library(MCAtools)
# Sample dataset
data <- data.frame(
Var1 = factor(sample(c("A", "B", "C"), 30, TRUE)),
Var2 = factor(sample(c("X", "Y", "Z"), 30, TRUE))
)
# Run MCA analysis
res <- mca\_analysis(data, delta = 1)
# Visualize MCA results
plot\_mca(res, plot\_type = "both")
# Generate symbolic equation
generate\_mca\_equation(res)Cressie, N. A., & Read, T. R. C. (1984). Goodness-of-Fit Statistics for Discrete Multivariate Data. Journal of the Royal Statistical Society, Series B (Methodological), 46(3), 440–464.
Maintainer: nona.kamdem@gmail.com
GPL-3