concorgmcano {BMconcor} | R Documentation |
Canonical analysis of subsets Yj with subsets Xi
Description
Canonical analysis of subsets Yj with subsets Xi. Relative valuations by squared correlations of the proximities of subsets Xi with subsets Yj. SUCCESSIVE SOLUTIONS
Usage
concorgmcano(x, px, y, py, r)
Arguments
x |
are the |
px |
The row vector which contains the numbers pi, i=1,...,kx, of the kx subsets xi of x : |
y |
See |
py |
The partition vector of y. A row vector containing the numbers |
r |
The number of wanted successive solutions rmax <= min(min(px),min(py),n) |
Details
For the first solution, sum_i sum_j \mbox{rho2}(cx_i[,1],cy_j[,1])
is the optimized
criterion. The other solutions are calculated from the same criterion, but with
orthogonalities for having two by two zero correlated the canonical components defined for
each xi, and also for those defined for each yj. Each solution associates kx canonical
components to ky canonical components. When kx =1 (px=p), take concorcano
function
This function uses the concorgm function
Value
A list
with following components:
cx |
is a |
cy |
is a |
rho2 |
is a |
Author(s)
Lafosse, R.
References
Kissita G., Analyse canonique generalisee avec tableau de reference generalisee. Thesis, Ceremade Paris 9 Dauphine (2003).
Examples
x <- matrix(runif(50),10,5);y <- matrix(runif(90),10,9)
x <- scale(x);y <- scale(y)
cc <- concorgmcano(x,c(2,3),y,c(3,2,4),2)
cc$rho2[1,1,]