concorscano function

simultaneous concorgmcano

concorgmcano with the set of r solutions simultaneously optimized

concorscano(x, px, y, py, r)

Arguments

• x: are the n times p and n times q matrices of p and q centered column
• 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 x
• py: The partition vector of y. A row vector containing the numbers qi for i = 1,...,ky of the ky subsets yi of y : sum(qi)=sum(py)=q.
• r: The number of wanted successive solutions rmax <= min(min(px),min(py),n)

Returns

A list with following components: - cx: a n times r matrix of the r canonical components of x

• cy: a n.ky times r matrix. The ky blocks cyi of the rows n*(i-1)+1 : n*i contain the r canonical components relative to Yi

• cov2: a ky times r matrix; each column k contains ky squared covariances $\mbox{cov}(x*u[,k],y_i*v_i[,k])^2$, the partial measures of link

Details

This function uses the concors function

Examples

x <- matrix(runif(50),10,5);y <- matrix(runif(90),10,9)
x <- scale(x);y <- scale(y)
cca <- concorscano(x,c(2,3),y,c(3,2,4),2)
cca$rho2[1,1,]

References

Hanafi & Lafosse (2001) Generalisation de la regression lineaire simple pour analyser la dependance de K ensembles de variables avec un K+1 eme. Revue de Statistique Appliquee vol.49, n.1

Author(s)