concorcano | R Documentation |
Relative proximities of several subsets of variables Yj with another set X. SUCCESSIVE SOLUTIONS
concorcano(x, y, py, r)
x |
are the |
y |
See |
py |
The partition vector of y. A row vector containing the numbers |
r |
The number of wanted successive solutions |
The first solution calculates a standardized canonical component cx[,1]
of x associated to ky
standardized components cyi[,1]
of yi by maximizing \sum_i \rho(cx[,1],cy_i[,1])^2
.
The second solution is obtained from the same criterion, with ky
orthogonality constraints for having rho(cyi[,1],cyi[,2])=0
(that
implies rho(cx[,1],cx[,2])=0)
. For each of the 1+ky sets, the r
canonical components are 2 by 2 zero correlated.
The ky matrices (cx)'*cyi are triangular.
This function uses concor function.
A list
with following components:
cx |
a |
cy |
a |
rho2 |
a |
Lafosse, R.
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
x <- matrix(runif(50),10,5);y <- matrix(runif(90),10,9)
x <- scale(x);y <- scale(y)
ca <- concorcano(x,y,c(3,2,4),2)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.