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Compositional Canonical Correlation Analysis

View ORCID ProfileJan Graffelman, Vera Pawlowsky-Glahn, Juan José Egozcue, Antonella Buccianti
doi: https://doi.org/10.1101/144584
Jan Graffelman
1Department of Statistics and Operations Research Universitat Politecnica de Catalunya Avinguda Diagonal 647, 08028 Barcelona, Spain.
2Department of Biostatistics University of Washington UW Tower, 15th Floor, 4333 Brooklyn Avenue NE Seattle 98105 WA, USA
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  • For correspondence: jan.graffelman@upc.es
Vera Pawlowsky-Glahn
3Department of Computer Science, Applied Mathematics, and Statistics Universitat de Girona Campus Montilivi, Edifici P4, E-17003 Girona, Spain.
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  • For correspondence: vera.pawlowsky@udg.edu
Juan José Egozcue
4Department of Civil and Environmental Engineering Universitat Politecnica de Catalunya Jordi Girona Salgado 1-3, Edifici C2, E-08034-Barcelona, Spain.
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  • For correspondence: juan.jose.egozcue@upc.edu
Antonella Buccianti
5Department of Earth Sciences University of Florence Via G. La Pira 4, 50121 Firenze, Italy
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  • For correspondence: antonella.buccianti@unifi.it
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Abstract

The study of the relationships between two compositions by means of canonical correlation analysis is addressed A coimnositional version of canonical correlation analysis is developed. and called CODA-CCO. We consider two approaches, using the centred log-ratio transformation and the calculation of all possible pairwise log-ratios within sets. The relationships between both approaches are pointed out, and their merits are discussed. The related covariance matrices are structurally singular, and this is efficiently dealt with by using generalized inverses. We develop compositional canonical biplots and detail their properties. The canonical biplots are shown to be powerful tools for discovering the most salient relationships between two compositions. Some guidelines for compositional canonical biplots construction are discussed. A geological data set with X-ray fluorescence spectrometry measurements on major oxides and trace elements is used to illustrate the proposed method. The relationships between an analysis based on centred log-ratios and on isometric log-ratios are also shown.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 31, 2017.
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Compositional Canonical Correlation Analysis
Jan Graffelman, Vera Pawlowsky-Glahn, Juan José Egozcue, Antonella Buccianti
bioRxiv 144584; doi: https://doi.org/10.1101/144584
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Compositional Canonical Correlation Analysis
Jan Graffelman, Vera Pawlowsky-Glahn, Juan José Egozcue, Antonella Buccianti
bioRxiv 144584; doi: https://doi.org/10.1101/144584

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