[R] Maximally independent variables

[Gabor Grothendieck]

That's basically what I already do but what I was wondering
was if there were any other approaches such as connections
with clustering, PCA, that have already been developed in
R that might be applicable.

On 3/1/06, Jacques VESLOT <jacques.veslot at cirad.fr> wrote:
> library(gtools)
> z <- combinations(ncol(DF), 3)
> maxcor <- function(x) max(as.vector(as.dist(cor(DF[,x]))))
> names(DF)[z[which.min(apply(z, 1, maxcor)),]]
>
>
> Gabor Grothendieck a écrit :
>
> >Are there any R packages that relate to the
> >following data reduction problem fo finding
> >maximally independent variables?
> >
> >Currently what I am doing is solving the following
> >minimax problem:  Suppose we want to find the
> >three maximally independent variables.  From the
> >full n by n correlation matrix, C, of all n variables
> >chooose three variables and form their 3 by 3 correlation
> >submatrix, C1, finding the offdiagonal entry of C1
> >which is largest in absolute value.  Call that z.  Thus for
> >each set of 3 variables we can associate such a z.
> >Now for each possible set of three variables find the one for
> >which its value of z is least.
> >
> >I only give the above formulation because that is
> >what I am doing now but I would be happy to
> >consider other different formulations.
> >
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> >
>
>