Latent structureMultivariate analysis

Robust Correspondence Analysis

Robust Correspondence Analysis (RCA) extends classical correspondence analysis to contingency tables that contain outlying rows or columns. By replacing the standard singular value decomposition with a robust alternative, RCA produces biplots and coordinate maps that accurately reflect the dominant association structure even when atypical cells or categories exert undue influence on the standard solution.

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Sources

  1. Croux, C. & Ruiz-Gazen, A. (2005). High breakdown estimators for principal components: the projection-pursuit approach revisited. Journal of Multivariate Analysis, 95(1), 206–226. DOI: 10.1016/j.jmva.2004.08.002
  2. Greenacre, M. (2017). Correspondence Analysis in Practice (3rd ed.). CRC Press / Chapman & Hall. ISBN: 978-1498731775

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Referenced by

ScholarGateRobust Correspondence Analysis (Robust Correspondence Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/statistics/robust-correspondence-analysis