edictive Co-Correspondence Analysis
#&gt; 
#&gt; Call: predcoca.eigen(y = y, x = x, R0 = weights, n.axes = n.axes,
#&gt; nam.dat = nam.dat)
#&gt; 
#&gt; Co-CA Method: eigen
#&gt; 
#&gt; 
#&gt; Eigenvalues:
#&gt; 
#&gt; 
#&gt;  COCA 1  COCA 2  COCA 3  COCA 4  COCA 5  COCA 6  COCA 7  COCA 8  COCA 9 COCA 10 
#&gt;   0.301   0.072   0.022   0.017   0.015   0.010   0.007   0.006   0.005   0.005 
#&gt; COCA 11 COCA 12 COCA 13 COCA 14 COCA 15 COCA 16 COCA 17 COCA 18 COCA 19 COCA 20 
#&gt;   0.004   0.004   0.003  