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Principal Component and Correspondence Analyses with Respect to Instrumental Variables : An Overview of Their Role in Studies of Structure - Activity and Species - Environment Relationships

  • J. D. Lebreton
  • R. Sabatier
  • G. Banco
  • A. M. Bacou
Part of the Eurocourses: Chemical and Environmental Science book series (EUCE, volume 2)

Abstract

Empirical studies of Structure - Activity Relationships (SAR, see, e.g., Doré and Miquel, 1981, Devillers and Karcher, 1990) and of Species - Environment Relationships (SER, see, e.g., Lebreton and Yoccoz, 1987, Jongman et al., 1987) share several striking characteristics. In both cases, one wishes to link the information in a first table X1 (Activity data, Species data) to the information in a second table X2 (Structure, Environment) obtained on the same statistical units as X1. X2 is supposed to influence X1. As a consequence any statistical approach should take account of this fundamental dissymmetry and should attempt to predict features in X1 from features in X2.

Keywords

Correspondence Analysis Instrumental Variable Canonical Correlation Analysis Statistical Unit Standardize Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1991

Authors and Affiliations

  • J. D. Lebreton
    • 1
  • R. Sabatier
    • 2
  • G. Banco
    • 1
  • A. M. Bacou
    • 1
  1. 1.Centre d’Ecologie Fonctionnelle et EvolutiveC.N.R.S.Montpellier CedexFrance
  2. 2.Laboratoire de Physique Industrielle PharmaceutiqueFaculté de PharmacieMontpellier CedexFrance

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