[R] LASSO coefficients for a specific s

[Bruno C.]

Hy,
no need to find the best s value. CV does it for you:
cvres<-cv.lars(X,Y,K=10,type='lasso')
sAtBest<-cvres$fraction[which.min(cvres$cv)]
fits <- predict.lars(object, type="coefficients", s=sAtBest, mode="fraction")

...
Ciao
Bruno

> Hello,
> 
> I have a question about the lars package. I am using this package to get the coefficients at a specific LASSO parameter s.
> 
> 
> data(diabetes)
> attach(diabetes)
> 
> object <- lars(x,y,type="lasso")
> 
> cvres<-cv.lars(x,y,K=10,fraction = seq(from = 0, to = 1, length = 100))
> 
> fits <- predict.lars(object, type="coefficients", s=0.1, mode="fraction")
> 
> 
> Can I assign automatically the best s value to predict.lars which is given by the CV process (cv.lars)? Or, do I need to manually find the s value that gives the minimum cv value from cv.lars, and assign it as the s value in predict.lars?
> 
> I would appreciate any advice on this. Thanks,
> Seungho Huh
> 
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