I know about glmmLasso but would prefer to use elastic net. I wonder if there are any glmm analogues of glmnet out there, or if anyone is working on any. I couldn't find any in my searches. Thanks


Maybe look at the MMS package. The lassop function seems to only be for lasso analysis, yet is clearly built on the glmnet package and includes some of its parameters such as alpha. If nothing else it is likely a good package to modify for your purposes.


  • $\begingroup$ 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? $\endgroup$
    – Randel
    Oct 29 '15 at 17:13
  • 1
    $\begingroup$ 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." $\endgroup$
    – Randel
    Oct 29 '15 at 19:34
  • $\begingroup$ Thank you Randel, that's actually quite helpful to me. The missing lambda parameter was what made me unsure. $\endgroup$
    – Danny
    Oct 29 '15 at 19:35
  • $\begingroup$ 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? $\endgroup$
    – Randel
    Oct 29 '15 at 19:42

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