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Oct 29, 2015 at 19:42 comment added Randel Yes, the author used a different name for this argument. Interestingly, the argument alpha shows it can do elastic net, but the function name and the descriptions are only related to lasso. Or the package is extended to elastic net but the description is not updated accordingly?
Oct 29, 2015 at 19:35 comment added Danny Thank you Randel, that's actually quite helpful to me. The missing lambda parameter was what made me unsure.
Oct 29, 2015 at 19:34 comment added Randel The answer is no. The tuning/regularization parameter is also needed in lassop(). According to the manual, "mu: Positive regularization number to be used for the Lasso."
Oct 29, 2015 at 17:13 comment added Randel Welcome to the site, @Danny! As you mentioned and is described in the link, "alpha : argument of ’glmnet’. The elasticnet mixing parameter, with 0 ≤ α ≤ 1. alpha=1 is the lasso penalty, and alpha=0 the ridge penalty." Though the function has the name lassop, as the examples use alpha=0.1, it works as elastic net. In terms of lasso, if I understand it correctly, the advantage of this package v.s. glmmlasso or lmmlasso is that the users do not need to select the tuning parameter lambda by themselves?
Oct 29, 2015 at 16:44 review Late answers
Oct 29, 2015 at 16:57
Oct 29, 2015 at 16:29 review First posts
Oct 29, 2015 at 16:38
Oct 29, 2015 at 16:24 history answered Danny CC BY-SA 3.0