Une méthode d'analyse canonique non linéaire et son application à des données biologiques
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 explanator...
Enregistré dans:
| Dans: | URI:https://journals.openedition.org/msh, |
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| Auteurs principaux: | , |
| Format: | Article ou chapitre numérique |
| Langue: | Français |
| Publié: |
Mathématiques et sciences humaines
2006
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| Accès en ligne: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |
| Résumé: | 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. |
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