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Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Quality statistics in canonical correspondence analysis
10.1002/env.481.abs
Canonical correspondence analysis is an important multivariate tool in ecology. A key aspect of the analysis is the representation of species optima, where these optima are estimated by the weighted averages of the species with respect to environmental variables. This article shows that, strictly speaking, canonical correspondence analysis does not optimize the representation of the species optima but the inertia of the abundance matrix under linear constraints. It is argued that the eigenvalues obtained in the analysis, usually reported in applied studies, are a measure of the quality of the display of the abundance matrix, and only indicate the quality of representation of the species optima when environmental variables are uncorrelated. In practice, environmental variables are often correlated. Thus, additional quality statistics are needed to express how well the species optima are represented. In this article we derive quality statistics for the representation of the species optima and the environmental variables, and use artificial and empirical data to illustrate their use. Copyright © 2001 John Wiley & Sons, Ltd.
Quality statistics in canonical correspondence analysis
10.1002/env.481.abs
Canonical correspondence analysis is an important multivariate tool in ecology. A key aspect of the analysis is the representation of species optima, where these optima are estimated by the weighted averages of the species with respect to environmental variables. This article shows that, strictly speaking, canonical correspondence analysis does not optimize the representation of the species optima but the inertia of the abundance matrix under linear constraints. It is argued that the eigenvalues obtained in the analysis, usually reported in applied studies, are a measure of the quality of the display of the abundance matrix, and only indicate the quality of representation of the species optima when environmental variables are uncorrelated. In practice, environmental variables are often correlated. Thus, additional quality statistics are needed to express how well the species optima are represented. In this article we derive quality statistics for the representation of the species optima and the environmental variables, and use artificial and empirical data to illustrate their use. Copyright © 2001 John Wiley & Sons, Ltd.
Quality statistics in canonical correspondence analysis
Graffelman, Jan (Autor:in)
Environmetrics ; 12 ; 485-497
01.08.2001
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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