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Choosing the number of principal coordinates when using CAP, the canonical analysis of principal coordinates

Citation

Ratkowsky, DA, Choosing the number of principal coordinates when using CAP, the canonical analysis of principal coordinates, Austral Ecology, 41, (7) pp. 842-851. ISSN 1442-9985 (2016) [Refereed Article]

Copyright Statement

Copyright 2016 Ecological Society of Australia

DOI: doi:10.1111/aec.12378

Abstract

This study explores various options available for choosing the number of principal coordinates m in the canonical analysis of principal coordinates ‘CAP’, a useful procedure that has wide-ranging application wherever multivariate data sets are collected or generated. Choosing too few coordinates (small m) in this constrained (i.e. hypothesis-based) ordination procedure may lead to inadequate separation of the groups (when used as a canonical discriminant analysis) or to inadequate correlation between explanatory and response variables (when used as a canonical correlations analysis), whereas choosing too many (large m) may lead to overparameterization, resulting in overfitting of the data and spurious relationships. It is shown here that the optimum number of principal coordinates is simply the one that results in the smallest P value in the canonical analysis carried out using permutations. For data in which more than one m value results in the same minimum P value, m should be chosen from that set to be the number of principal coordinates that minimizes the leave-one-out residual sum of squares. This choice of m provides suitable solutions for each of the 17 case studies investigated here (which yielded 17 canonical discriminant analyses and 7 canonical correlation analyses).

Item Details

Item Type:Refereed Article
Keywords:canonical correlations, constrained ordination, discriminant analysis, dissimilarity measures, distance measure, multivariate cloud
Research Division:Mathematical Sciences
Research Group:Applied Mathematics
Research Field:Biological Mathematics
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Mathematical Sciences
Author:Ratkowsky, DA (Dr David Ratkowsky)
ID Code:111953
Year Published:2016
Web of Science® Times Cited:1
Deposited By:Tasmanian Institute of Agriculture
Deposited On:2016-10-17
Last Modified:2017-11-01
Downloads:0

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