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$beta)^2)/var(y)*19 #I have 20 observations...my R2 is lower than the one here Thanks a lot -- View this message in context: http://r.789695.n4.nabble.com/the-output-of-function-lars-tp3078460p3078460.html Sent from the R help mailing list archive at Nabble.com.
I think the authors of lars could do a better job of the 'Value' section of the help page. Nevertheless, most of the list elements are pretty obvious if you understand the LARS procedure. Your questions indicate that you would benefit from studying the references listed on the help page before attempting to use the lars package. I can recommend the book 'The Elements of Statistical Learning'. Peter Ehlers On 2010-12-08 08:02, poko2000 wrote:> > Hi here is the code as example > lars is in package lars >> x<-matrix(rnorm(20*5,0,1),20,5) >> bs<-matrix(sample(seq(1:10),5),5,1) >> er<-rnorm(20,0,1) >> y<-x%*%bs+er >> lobj<-lars(x,y,type="lasso") >> names(lobj) > [1] "call" "type" "df" "lambda" "R2" > [6] "RSS" "Cp" "actions" "entry" "Gamrat" > [11] "arc.length" "Gram" "beta" "mu" "normx" > [16] "meanx" > > I do not know what does RSS, arc.length, mu mean??? > If mu means \hat{miu}, it does not seems to be right. I did not simulate my > data with mean. > > besides I caculated R2 by myself but it cannot match the R2here > I think R2=1-sum((y-x%*%lobj$beta)^2)/var(y)*19 #I have 20 observations...my > R2 is lower than the one here > > Thanks a lot > > >
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