Multiple Factor Analysis (MFA) dedicated to datasets where variables are organized into groups (qualitative and/or quantitative variables). Multiple Correspondence Analysis (MCA), which is an adaptation of CA to a data table containing more than two categorical variables. Principal Component Analysis (PCA), which is used to summarize the information contained in a continuous (i.e, quantitative) multivariate data by reducing the dimensionality of the data without loosing important information.Ĭorrespondence Analysis (CA), which is an extension of the principal component analysis suited to analyse a large contingency table formed by two qualitative variables (or categorical data).
Factoextra : Extract and Visualize the Results of Multivariate Data Analysesįactoextra is an R package making easy to extract and visualize the output of exploratory multivariate data analyses, including:
