Comparer des méthodes

	Analyse des Correspondances	L'Échelle multidimensionnelle (MDS)
Domaine	Statistique	Statistique
Famille	Latent structure	Latent structure
Année d'origine	1984	1952–1964
Auteur d'origine	Jean-Paul Benzécri; Michael Greenacre	Warren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964)
Type	Exploratory multivariate technique for categorical data	Dimensionality reduction / visualization
Source fondatrice	Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2	Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27.
Alias	CA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum Analizi	MDS, metric MDS, non-metric MDS, proximity scaling
Apparentées	2	5
Résumé	Correspondence Analysis (CA) is an exploratory multivariate technique for visualizing the association structure of a two-way contingency table. Developed systematically by Jean-Paul Benzécri in France during the 1960s–1970s and brought to an English-language audience by Michael Greenacre in 1984, CA decomposes the chi-square statistic of a cross-tabulation to produce a low-dimensional joint display — called a biplot — in which rows and columns are represented as points whose proximities reflect their associations.	Multidimensional scaling maps objects described only by pairwise similarities or dissimilarities into a low-dimensional geometric space so that distances in that space reflect the original proximity structure as faithfully as possible. It is widely used to visualize the hidden structure of psychological, social, and behavioral data.