You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
It would make sense to have a main argument for the select argument:
select: If this is TRUE then gam can add an extra penalty to each term so that it can be penalized to zero. This means that the smoothing parameter estimation that is part of fitting can completely remove terms from the model. If the corresponding smoothing parameter is estimated as zero then the extra penalty has no effect. Use gamma to increase level of penalization.
and
gamma: Increase this beyond 1 to produce smoother models. gamma multiplies the effective degrees of freedom in the GCV or UBRE/AIC. coden/gamma can be viewed as an effective sample size in the GCV score, and this also enables it to be used with REML/ML. Ignored with P-RE/ML or the efs optimizer.
Maybe use select_features for select and adjust_deg_free for gamma?
The text was updated successfully, but these errors were encountered:
I agree too! I actually wasn't aware that we can apply smooths to all of features. I do have a couple questions about factors since I'm wondering how the s() "by" argument works when automating but this is some research on my part.
It would make sense to have a main argument for the
select
argument:and
Maybe use
select_features
forselect
andadjust_deg_free
forgamma
?The text was updated successfully, but these errors were encountered: