Iconography of correlations

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Representation of the proximity of food profiles in Europe.

In exploratory data analysis, the iconography of correlations,[1][2] or representation of correlations, is a data visualization technique which replaces a numeric correlation matrix by its graphical projection onto a diagram, on which the “remarkable” correlations are plotted as solid lines (positive correlations) or dotted lines (negative correlations); either shorter lengths, or thicker lines, or both, represent greater correlation projection components.


This idea is used in Gaussian graphic models for genome mapping, particularly. But the iconography of correlations is more general, since it does not assume that the data is Gaussian; it only relies on representing the correlation coefficients geometrically.

The iconography of correlations first dates to 1975, applied to marine geochemistry in a 1981 thesis,[citation needed] and later in a 1982 data analysis article.[3] Afterward, the method was applied widely in the aerospace industry[4][5] but for about fifteen years manufacturers kept it fairly confidential; generally, they preferred to not broadcast useful techniques to their competitors.

In 1997 the first company was incorporated to distribute iconography of correlations software.[6] Since then the topic of iconography of correlations has been incorporation into some university courses, and typical topical articles' citation lists have rapidly and greatly expanded, particularly in the fields of medicine[7] and mass spectrometry.[8][9][10]

See also

  • Bayesian network — a graph in which cause and effect are measured probabilisticly instead of geometricly as in correlation iconography.


  1. Lesty, Michel (January 1999). "Une nouvelle approche dans le choix des régresseurs de la régression multiple en présence d'interactions et de colinéarités" (in fr). La Revue de Modulad (22): 41–77. http://www-rocq.inria.fr/axis/modulad/archives/numero-22/Lesty-22/unenouvelle.pdf. 
  2. Girondot, Marc (17 January 2018). "Multivariable analysis and correlation of iconography". https://biostatsr.blogspot.com/2018/01/multivariable-analysis-and-correlation.html. "... about biostatistics ... by Professor Marc Girondot, University Paris Saclay."  — Brief inroduction to iconography of correlations.
  3. Lesty, M.; Buat-Ménard, P. (1982). "La synthèse géométrique des corrélations multidimensionnelles" (in fr). Les Cahiers de l'Analyse des Données [Data Analysis Notes] VII (3): 355–370. http://www.coryent.com/Lesty-CahierADVII-1982n3.pdf. 
  4. Lesty, M.; Coindoz, M. (3–7 October 1988). "Une méthode pour la F.M.S. des bases de connaissances de système experts. Une application de CORICO". 6e Colloque International de Fiabilité et de Maintenabilité. Strasbourg, DE: Centre National d'Études Spatiales (CNES). pp. 252–257. 
  5. Vallée, C.; le Méteil, X. (Fourth Quarter 2001), "La maîtrise du risque dans la construction aéronautique: Analyse des corrélations et fabrication des composites" (in fr), Phoebus 19 (2) 
  6. Lesty, Michel, ed. "La Société CORYENT Conseil / Etudes et conseil" (in fr). CORYENT Conseil / Logiciel CORICO. https://www.coryent.com/mlesty.html. "CORYENT Conseil est une entreprise française de conseil, fondée en 1997 par Michel Lesty, ..."
    "[CORYENT Conseil is a French consulting company, founded in 1997 by Michel Lesty, ...]"
  7. Lesty, C.; Pleau-Varet, J.; Kujas, M. (February 2004). "Geometric method and generalized linear models: Two opposite multiparametric approaches illustrated on a sample of pituitary adenomas". Journal of Applied Statistics 31 (2): 191–213. 
  8. Engrand, C.; Lespagnol, J.; Martin, P.; Thirkell, L.; Thomas, R. (2004). "Multi-correlation analyses of TOF-SIMS spectra for mineralogical studies". Applied Surface Science (231–232): 883–887. 
  9. Engrand, C.; Kissel, J.; Krueger, F.R. et al. (2006). "Chemometric evaluation of time-of-flight secondary ion mass spectrometry data of minerals in the frame of future in situ analyses of cometary material by COSIMA onboard ROSETTA" (in en). Rapid Communications in Mass Spectrometry 20 (8): 1361–1368. 
  10. Paillat, Louise; Cannavo, Patrice; Barraud, Fabrice; Huché-Thélier, Lydie; Guénon, René (December 2020). "Growing medium type affects organic fertilizer mineralization and CNPS microbial enzyme activity" (in en). Agronomy 10 (12): 1955. doi:10.3390/agronomy10121955. 

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