(11/03/25 22:40), Nick Sabbe wrote: > 2. Which model, I mean lasso or elastic net, should be selected? and > why? Both models chose the same variables but different coefficient values. > You may want to read 'the elements of statistical learning' to find some > info on the advantages of ridge/lasso/elnet compared. Lasso should work fine > in this relatively low-dimensional setting, although it depends on the > correlation structure of your covariates.
I also checked correlation structure of my covariates. test <- lm(y ~ x15std) library(DAAG) vif(test) x15std1 x15std2 x15std3 x15std4 x15std5 x15std6 x15std7 x15std8 x15std9 x15std10 x15std11 x15std12 x15std13 x15std14 1.2299 1.2880 1.1011 1.1559 1.3033 1.0774 1.5369 1.9604 1.4664 1.1754 1.1396 1.2683 1.1685 1.1667 x15std15 1.5534 Variance inflation are less than 5 suggesting that multicollinearity is unlikely to be a problem. Therefore, Lasso model should be selected? Thanks a lot in advance, KH ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
