Two-block Partial Least squares can be seen as an ordination method comparable with PCA, but with the objective of maximizing covariance between two sets of variates on the same rows (specimens, sites). For example, morphometric and environmental data collected on the same specimens can be ordinated in order to study covariation between the two.
The program will ask for the number of columns belonging to the first block. The remaining columns will be assigned to the second block. There are options for plotting PLS scores both within and across blocks, and PLS loadings. Biplots are not yet implemented. The algorithm follows Rohlf & Corti (2000).
The permutation test permutes cases (rows) for one of the sets of variables, and reports the p values for the covariances.
Missing data supported by column average substitution.
References
Rohlf, F.J. & M. Corti. 2000. Use of two-block partial least squares to study covariation in shape. Systematic Biology 49:740-753.