# Maximally independent variables

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## Maximally independent variables

 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. ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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## Re: Maximally independent variables

 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. > >______________________________________________ >[hidden email] mailing list >https://stat.ethz.ch/mailman/listinfo/r-help>PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html> >   > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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## Re: Maximally independent variables

 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 <[hidden email]> 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. > > > >______________________________________________ > >[hidden email] mailing list > >https://stat.ethz.ch/mailman/listinfo/r-help> >PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html> > > > > > > > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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## Re: Maximally independent variables

 In case others are interested I did get a reply offlist regarding the escouf function in the pastecs package. See:    library(pastecs)    ?escouf Also see pages 47-52 of    system.file("doc/pastecs.pdf", package = "pastecs") (in French). On 3/1/06, Gabor Grothendieck <[hidden email]> wrote: > 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 <[hidden email]> 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. > > > > > >______________________________________________ > > >[hidden email] mailing list > > >https://stat.ethz.ch/mailman/listinfo/r-help> > >PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html> > > > > > > > > > > > > > ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html