Subject: glm and stepAIC selects too many effects
See package "glmnet". -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Tue, Jun 6, 2017 at 8:10 AM, Ravi Varadhan <ravi.varadhan at jhu.edu> wrote:
More principled would be to use a lasso-type approach, which combines selection and estimation in one fell swoop! Ravi
________________________________
From: Ravi Varadhan
Sent: Tuesday, June 6, 2017 10:16 AM
To: r-help at r-project.org
Subject: Subject: [R] glm and stepAIC selects too many effects
If AIC is giving you a model that is too large, then use BIC (log(n) as the penalty for adding a term in the model). This will yield a more parsimonious model. Now, if you ask me which is the better option, I have to refer you to the huge literature on model selection.
Best,
Ravi
[[alternative HTML version deleted]]
______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.