Analyzing a set of partial links between Xi and Yj, SUCCESSIVE SOLUTIONS
1  concorgm(x,px,y,py,r)

x 
is a n x p matrix of p centered variables 
y 
is a n x q matrix of q centered variables 
px 
is a row vector which contains the numbers pi, i=1,...,kx, of the kx subsets xi of x : sum(pi)=sum(px)=p. px is the partition vector of x 
py 
is the partition vector of y with ky subsets yj, j=1,...,ky 
r 
is the wanted number of successive solutions rmax <= min(min(px),min(py),n) 
For the first solution, ∑_i ∑_j \mbox{cov2}(x_i*u_i[,1],y_j*v_j[,1]) is the optimized criterion. The second solution is calculated from the same criterion, but with x_ix_i*u_i[,1]*u_i[,1]' and y_jy_j*v_j[,1]*v_j[,1]' instead of the kx+ky matrices xi and yj. And so on for the other solutions. When kx=1 (px=p), take concor.m
This function uses the svdbip function.
list with following components
u 
is a p x r matrix of kx row blocks ui (pi x r), the orthonormed partial axes of xi; associated partial components: xi*ui 
v 
is a q x r matrix of ky row blocks vj (qj x r), the orthonormed partial axes of yj; associated partial components: yj*vj 
cov2 
is a kx x ky x r array; for r fixed to k, the matrix contains kxky squared covariances \mbox{cov2}(x_i*u_i[,k],y_j*v_j[,k])^2, the partial links between xi and yj measured with the solution k. 
Kissita, Cazes, Hanafi & Lafosse (2004) Deux methodes d'analyse factorielle du lien entre deux tableaux de variables partitionn<e9>es. Revue de Statistique Appliqu<e9>e, Vol 52, n<b0> 3, 7392.
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