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The contributions of rare objects in correspondence analysis.
1Department of Economics and Business, Barcelona Graduate School of Economics, Universitat Pompeu Fabra, 08005 Barcelona, Spain. michael.greenacre@upf.edu
Ecology
|April 23, 2013
Summary
Correspondence analysis is robust to rare species, as their low weight balances their outlier positions. A new contribution biplot visualization is proposed for ecological data analysis.
Area of Science:
- Ecology
- Multivariate statistics
Background:
- Correspondence analysis (CA) is widely used for analyzing ecological count data.
- Concerns exist regarding CA's sensitivity to rare species, potentially skewing results.
Purpose of the Study:
- To evaluate the actual influence of rare species on correspondence analysis and canonical correspondence analysis.
- To propose an improved visualization method for handling rare species in ordination.
Main Methods:
- Calculated contributions of rare objects (species) to ordination axes and chi-square distances.
- Employed correspondence analysis (CA) and canonical correspondence analysis (CCA).
- Developed and applied a contribution biplot scaling for CA and triplot for CCA.
Main Results:
- Criticism of CA's sensitivity to rare species is largely unfounded.
- Rare species, while often outliers, have low statistical weight, minimizing their influence on overall results.
- The proposed contribution biplot visually represents species contributions directly through point coordinates.
Conclusions:
- Correspondence analysis is a reliable method for ecological data, even with rare species.
- The contribution biplot offers a more informative visualization for understanding species contributions in ordination.
- This method enhances the interpretation of ecological community structures derived from multivariate analysis.
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