As a first example, consider again the data set presented in Table 10.5. The first five variables are assembled into matrix Y and the three spatial variables make up matrix X. Calculations performed as described above, or using the iterative algorithm
Table 11.1 Maximum number of non-zero eigenvalues and corresponding eigenvectors that may be obtained from canonical analysis of a matrix of response variables Y(n x p) and a matrix of explanatory variables X(n x m) using redundancy analysis (RDA) or canonical correspondence analysis (CCA).
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