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Extensions of Correspondence Analysis for the Statistical Exploration of Multidimensional Contingency Tables

  • Renate Meyer
Conference paper

Abstract

In this paper four different generalizations of canonical correlation analysis to Q ≥ 3 sets of random variables are proposed, their application to indicator variables is studied, and the resulting extensions of correspondence analysis (CA) to Q-dimensional contingency tables are presented. The determination of canonical variates leads to generalized eigenvalue problems which can be solved using a globally convergent algorithm, based on Watson’s iteration.

Keywords

Correspondence Analysis Canonical Correlation Canonical Correlation Analysis Canonical Variate Generalize Eigenvalue Problem 
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References

  1. Carroll, J.D. (1968): Generalization of Canonical Correlation Analysis to three or more sets of variables. Proc. 76th annual convention of the APA, 227–228. Google Scholar
  2. Greenacre, M. J. (1984): Theory and Applications of Correspondence Analysis. Academic Press, New York. MATHGoogle Scholar
  3. Häussler, W. M. (1984): Computational Experience with an EV Algorithm for robust Lp-Discrimination. Comp. Stat. Quaterly 1, 288–244 Google Scholar
  4. Kettenring, J. R. (1971): Canonical Analysis of several sets of variables. Biometrika 58, 488–51. MathSciNetCrossRefGoogle Scholar
  5. Lebart, L., Morineau, A., Fenelon, J.-P. (1979): Traitement des Données Statistiques. Dunod, Paris. MATHGoogle Scholar
  6. Watson, G. A. (1985): On the Convergence of EV Algorithms for Robust lp-Discrimination. Comp. Stat. Quarterly 4, 807–14. Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1989

Authors and Affiliations

  • Renate Meyer
    • 1
  1. 1.Institut für Medizinische Statistik und Dokumentation der RWTH AachenGermany

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