[R] glmnet vignette question

Dominik Schneider dominik.schneider at colorado.edu
Fri Sep 16 18:33:53 CEST 2016

> Is there a way to extract MSE for a lambda, e.g. lambda.1se?
nevermind this specific question. it's now obvious. However my overall
question stands.

On Fri, Sep 16, 2016 at 10:10 AM, Dominik Schneider <
dominik.schneider at colorado.edu> wrote:

> I'm doing some linear modeling and am new to the ridge/lasso/elasticnet
> procedures. In my case I have N>>p (p=15 based on variables used in past
> literature and some physical reasoning) so my understanding is that I
> should be interested in ridge regression to avoid the issue of
> multicollinearity of predictors.  Lasso is useful when p>>N.
> In the past I have performed step-wise regression with stepAIC in both
> directions to choose my variables and then used VIF to determine if any of
> these variables are correlated. My understanding is that ridge regression
> is a more robust approach for this workflow.
> Reading the glmnet_beta vignette, it describes the alpha parameter where
> alpha=1 is a lasso regression and alpha=0 is a ridge regression. Farther
> down the authors suggest a 10 fold validation to determine an alpha value
> and based on the plots shown, say that alpha=1 does the best here. However,
> all the models look like they approach the same MSE and alpha=0 is the
> lowest curve for all lambda (but maybe this second point doesn't matter?).
> With my data I get a very similar looking set of curves so I'm trying to
> decide if I should stick with alpha=1 instead of alpha=0. Is there a way to
> extract MSE for a lambda, e.g. lambda.1se?
> Any advice or clarification is appreciated. Thanks.
> Dominik

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