R help - Nov 2004 - how to compute condition index?

is there any existing function for computing condition index?
" analysing multivariate data" say that we can use condition index to
check
multicollinearity.saying that we can get it via SVD. The elements of the 
diagnoal matrix are the standard deviations of the uncorrelated vectors. the 
condition index is the ratio of the largest of these numbers to the smallest.
so if i have a data frame a,containg variables x,y,z.
my model is :
model<-lm(y~x+z,data=a)
so use the following to compute the condition index,but it seems wrong.

temp<-svd(model.matrix(model))$d
max(temp)/min(temp)

is it wrong?

--- rongguiwong <0034058 at fudan.edu.cn> wrote:
> is there any existing function for computing condition index?
I've written a function called "colldiag" that calculates
condition
indexes and variance decomposition proportions. It's available at
http://www.xs4all.nl/~jhckx/R/perturb/. I plan to add some features
to the "perturb" and "reclassify" functions, then upload the
package
to CRAN. Until then, it's only available from my website. 

Good luck,
John Hendrickx



		
__________________________________

rongguiwong wrote:
>is there any existing function for computing condition index?
>  
>
See
?kappa

Kjetil
>" analysing multivariate data" say that we can use condition index
to check
>multicollinearity.saying that we can get it via SVD. The elements of the 
>diagnoal matrix are the standard deviations of the uncorrelated vectors. the
>condition index is the ratio of the largest of these numbers to the
smallest.
>so if i have a data frame a,containg variables x,y,z.
>my model is :
>model<-lm(y~x+z,data=a)
>so use the following to compute the condition index,but it seems wrong.
>
>temp<-svd(model.matrix(model))$d
>max(temp)/min(temp)
>
>is it wrong?
>
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>
>
>  
>

-- 

Kjetil Halvorsen.

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