concorscano: "simultaneous concorgmcano"
In concor: Concordance

Description Usage Arguments Details Value References Examples

concorgmcano with the set of r solutions simultaneously optimized

1	concorscano(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 : ∑_i p_i=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)

This function uses the concors function

list with following components

`cx`	is a n.kx x r matrix of kx row blocks cxi (n x r). Each row block contains r partial canonical components
`cy`	is a n.ky x r matrix of ky row blocks cyj (n x r). Each row block contains r partial canonical components
`rho2`	is a kx x ky x r array; for a fixed solution k, rho2[,,k] contains kxky squared correlations ρ(cx[n(i-1)+1:ni,k],cy[n(j-1)+1:nj,k])^2, simultaneously calculated between all the yj with all the xi

See svdbips

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)
diag(t(cca$cx[1:10,])%*%cca$cy[1:10,]/10)^2
cca$rho2[1,1,]