I think the authors of lars could do a better job of
the 'Value' section of the help page. Nevertheless, most
of the list elements are pretty obvious if you
understand the LARS procedure. Your questions indicate
that you would benefit from studying the references
listed on the help page before attempting to use the
lars package. I can recommend the book 'The Elements
of Statistical Learning'.
Peter Ehlers
On 2010-12-08 08:02, poko2000 wrote:
Hi here is the code as example
lars is in package lars
x<-matrix(rnorm(20*5,0,1),20,5)
bs<-matrix(sample(seq(1:10),5),5,1)
er<-rnorm(20,0,1)
y<-x%*%bs+er
lobj<-lars(x,y,type="lasso")
names(lobj)
[1] "call" "type" "df" "lambda" "R2"
[6] "RSS" "Cp" "actions" "entry" "Gamrat"
[11] "arc.length" "Gram" "beta" "mu" "normx"
[16] "meanx"
I do not know what does RSS, arc.length, mu mean???
If mu means \hat{miu}, it does not seems to be right. I did not simulate my
data with mean.
besides I caculated R2 by myself but it cannot match the R2here
I think R2=1-sum((y-x%*%lobj$beta)^2)/var(y)*19 #I have 20 observations...my
R2 is lower than the one here
Thanks a lot
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