Determines the scores on the dependent and the independent canonical variates from the selected CCA and TableOfReal objects.

Settings

Number of canonical correlations

determines the dimension, i.e., the number of elements of the resulting canonical score vectors. The newly created table will have twice this number of columns because we have calculated score vectors for the dependent and the independent variates.

Behaviour

The scores on the dependent set are determined as T_y Y, where T_y is the dependent part in the table and Y is a matrix with numberOfCanonicalCorrelations eigenvectors for the dependent variate.

The scores for the independent variates are then determined in an analogous way as T_x X.

The scores for the dependent data will be in the lower numbered columns, the scores for the independent part will be in the higher numbered columns of the newly created object.

Links to this page

• Canonical correlation analysis