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Analisis Korespondensi×Multidimensional Scaling (MDS)×
BidangStatistikaStatistika
KeluargaLatent structureLatent structure
Tahun asal19841952–1964
PencetusJean-Paul Benzécri; Michael GreenacreWarren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964)
TipeExploratory multivariate technique for categorical dataDimensionality reduction / visualization
Sumber perintisGreenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27. DOI ↗
AliasCA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum AnaliziMDS, metric MDS, non-metric MDS, proximity scaling
Terkait25
RingkasanCorrespondence 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.
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ScholarGateBandingkan metode: Correspondence Analysis · Multidimensional Scaling. Diakses 2026-06-17 dari https://scholargate.app/id/compare