concorsreg: "simultaneous concorgmreg"
In concor: Concordance

Description Usage Arguments Details Value References Examples

concorgmreg with the set of r solutions simultaneously optimized

1	concorsreg(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)

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 explanatory components
`v`	is a q x r matrix of ky row blocks vj (qj x r), the orthonormed partial axes of yj; The components yj*vj are the explained components.
`varexp`	is a kx x ky x r array; for a fixed solution k, the matrix varexp[,,k] contains kxky explained variances obtained by a simultaneous regression of all the yj by all the xi, so the values \mbox{rho2}(cx[n(i-1)+1:ni,k],y_jv_j[,k]) var(y_jv_j[,k])

See svdbips

x<-matrix(runif(50),10,5);y<-matrix(runif(90),10,9)
x<-scale(x);y<-scale(y)
crs<-concorsreg(x,c(2,3),y,c(3,2,4),2)
diag(t(crs$cx[1:10,])%*%y[,1:3]%*%crs$v[1:3,]/10)^2
crs$varexp[1,1,]