Dear R-users
I'm trying to use lasso in lars package for subset regression, I have a
large matrix of size 1000x100 and my aim is to select a subset k of the 100
variables.
Is there any way in lars to fix the number k (i.e. to select the best 10
variables)
library(lars)
aa=lars(X,Y,type="lasso",max.steps=200)
plot(aa,plottype="Cp")
aa$RSS
which.min(aa$RSS)
round(aa$beta,2)
aa$beta[which.min(aa$RSS),] # find which coefficients minimizes the RSS
lasso.ind=which((as.vector((aa$beta[which.min(aa$RSS),])))>0) # index of
variables
print(lasso.ind) # this usually gives more than 10 variables (also depends
on the max.steps in lars)
Thanks in advance
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