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Analyse canonique de redondance (redundancy analysis: RDA)

5 Juillet 2010,

Publié par JMB

Une méthode d'analyse canonique non linéaire et son application à des données biologiques

Un article de Vladimir Makarenkov et Pierre Legendre paru dans Math. Inf. Sci. Hum, (n°147, 1999, pp. 135-147)


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A method of nonlinear canonical analysis and its application to biological data

Among the various forms of canonical analysis available in the statistical literature, RDA (redundancy analysis) has become an instrument of choice for ecological analysis. A first data table (Y) contains the response variables (e.g. species data) whereas the second table (X) contains the explanatory variables (e.g. environmental variables). Classical RDA assumes that the relationships between variables in X and Y are linear ; this is unrealistic in most cases. We propose a new ordination method, called polynomial RDA, to do away with the constraints of linearity in these relationships. Polynomial RDA is based on an empirical regression algorithm which allows polynomial relationships to be modelled between the variables in X and Y ; it also takes into account the relationships among the explanatory variables.


Analyse canonique de redondance (redundancy analysis: RDA)

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