Re: [R] gam() (in mgcv) with multiple interactions

Dear Simon, I have the same problem. I understand te(a), te(b) are nested in te(a,b) according to your paper on tensor product. I have no enough data to perform te(a,b,d) and only care the interactions a*b and a*d, so I did y=te(a,b)+te(a,d). The resutl is good. I am wondering if this is the co

Re: [R] gam() (in mgcv) with multiple interactions

your help! Ben Haller McGill University http://biology.mcgill.ca/grad/ben/ Begin forwarded message: > From: Simon Wood > Date: June 9, 2011 11:35:11 AM EDT > To: r-help@r-project.org, rh...@sticksoftware.com > Subject: Re: [R] gam() (in mgcv) with multiple interactions > >

Re: [R] gam() (in mgcv) with multiple interactions

I think that the main problem here is that smooths are not constrained to pass through the origin, so the covariate taking the value zero doesn't correspond to no effect in the way that you would like it to. Another way of putting this is that smooths are translation invariant, you get essentia

[R] gam() (in mgcv) with multiple interactions

Hi! I'm learning mgcv, and reading Simon Wood's book on GAMs, as recommended to me earlier by some folks on this list. I've run into a question to which I can't find the answer in his book, so I'm hoping somebody here knows. My outcome variable is binary, so I'm doing a binomial fit with