concorgmreg | R Documentation |
Regression of subsets Yj by subsets Xi for comparing all the explanatory-explained pairs (Xi,Yj). SUCCESSIVE SOLUTIONS
concorgmreg(x, px, y, py, r)
x |
are the |
px |
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 |
y |
See |
py |
The partition vector of y. A row vector containing the numbers |
r |
The number of wanted successive solutions |
For the first solution, \sum_i \sum_j \mbox{rho2}(cx_i[,1],y_j*v_j[,1])
\mbox{var}(y_j*v_j[,1])
is the optimized criterion. The second solution is
calculated from the same criterion, but with y_j-y_j*v_j[,1]*v_j[,1]'
instead of the matrices yj and with orthogonalities for having two by
two zero correlated the explanatory components defined for each matrix
xi. And so on for the other solutions. One solution k associates kx
explanatory components (in cx[,k]
) to ky explained components. When
kx =1 (px = p), take concoreg function
This function uses the concorgm function
A list
with following components:
cx |
a |
v |
is a |
varexp |
is a kx x ky x r array; for a fixed solution k, the matrix |
Lafosse, R.
Hanafi & Lafosse (2004) Regression of a multi-set by another based on an extension of the SVD. COMPSTAT'2004 Symposium
x <- matrix(runif(50),10,5);y <- matrix(runif(90),10,9)
x <- scale(x);y <- scale(y)
cr <- concorgmreg(x,c(2,3),y,c(3,2,4),2)
cr$varexp[1,1,]
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