Thanks for the email. I will check that out....
However when I was doing this : gam(y~s(x1)+s(x2,3), family=gaussian,
data=mydata )it gives me the error :
"Error in terms.formula(formula, data = data) :
invalid model formula in ExtractVars"
What does it mean ?
Thanks
-Janice
-----Original Message-----
From: Liaw, Andy [mailto:[EMAIL PROTECTED]
Sent: Sunday, December 05, 2004 11:34 PM
To: 'Janice Tse'; [EMAIL PROTECTED]
Subject: RE: [R] Gam() function in R
Unfortunately that's not really an R question. I recommend that you read up
on the statistical methods underneath. One that I'd wholeheartedly
recommend is Prof. Harrell's `Regression Modeling Strategies'.
[BTW, there are now two implementations of gam() in R: one in `mgcv', which
is fairly different from that in `gam'. I'm guessing you're referring to
the one in `gam', but please remember to state which contributed package
you're using, along with version of R and OS.]
Cheers,
Andy
> From: Janice Tse
>
> Hi all,
>
> I'm a new user of R gam() function. I am wondering how do
> we decide on the
> smooth function to use?
> The general form is gam(y~s(x1,df=i)+s(x2,df=j).......) , how do we
> decide on the degree freedom to use for each smoother, and if we shold
> apply smoother to each attribute?
>
> Thanks!!
>
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