Procrustean co-inertia analysis for the linking of multivariate datasets

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Intensification of agriculture, landscape composition and wild bee communities: a large scale study in four European countries. (2010, methodology): “These analyses were performed in three steps: (i) correspondence analysis (CA) on the species abundance per site (14 sites 71 bee species); (ii) principal component analysis (PCA) on the quantitative agricultural data (14 sites eight variables, see Table 1); (iii) co-inertia analysis, which is parti”
CO‐INERTIA ANALYSIS AND THE LINKING OF ECOLOGICAL DATA TABLES (2003, methodology): “We measure the fit between original data and ordination results by m, the sum of singular values of procrustes analysis (Jackson 1995, Dray et al. 2003).”
Spatial ordination of vegetation data using a generalization of Wartenberg's multivariate spatial correlation (2008, methodology): “For a review in ecology, the reader should consult Dray et al. (2003a).”
Dimensions and their poles: A metric and topological approach to opposites (2011, methodology): “…9 and 12 into Procrustean agreement (i.e., the corresponding 1250 BIANCHI ET AL. matrices are rotated to maximum similarity by minimising the sum of the squared differences between them, by the method proposed by Dray et al., 2003, implemented in the R package ade4; see Dray & Dufour, 2007).”