# Robust GAM that covers Gaussian distribution

I was looking at CrossValidate archives as well as r-archives and crantastic...for a package that has a robust approach to generalized additive models. I found two packages "robustgam" and "rgam" but their implemented functions cover only binomial and Poisson distributions (pls correct me if I am wrong).

I would greatly appreciate if anyone could share with us other R-packages or robust approaches of general additive modeling that might have a better performance with small data sets ($n<100$ records or 50 -100 records).

• Interesting thought...I am not sure but sounds that it might work! Did you have in mind a specific pacgage like mgcv, or robustgam or rgam? Thank you VERY MUCH for your immediate response. I sincerely appreciate it. – user22478 Jun 2 '13 at 23:43
• no, that was wrong... – user603 Jun 3 '13 at 5:39
• yes...thank you any new ideas? – user22478 Jun 3 '13 at 18:06

• @Dave The scat family in mgcv doesn't allow for a linear predictor (beyond an intercept) for $\nu$; in general though, one could have a model for $\nu$. The VGAM, gamlss packages allow for this as do more general packages like brms*/*Stan etc – Gavin Simpson Mar 20 '20 at 22:54
• But see stats.stackexchange.com/questions/45784/…, MASS (the book) advices against trying to estimate $\nu$, it looses robustness. – kjetil b halvorsen Mar 21 '20 at 0:50