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
, jari oksanen
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
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?
I guess you
-Original Message-
From: Simon Wood [mailto:[EMAIL PROTECTED]
Sent: Monday, December 06, 2004 5:54 AM
To: Janice Tse
Cc: [EMAIL PROTECTED]
Subject: Re: [R] Gam() function in R
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
At 10:48 2004-12-06 +0100, Yves Magliulo wrote:
this subject is very intersting for me. I'm using mgcv 0.8-9 with R
version 1.7.1.
You're in need of an update.
i didn't know that there was an another gam version with
package library(gam).
This is the 'classic' GAM implementation by Hastie
this subject is very intersting for me. I'm using mgcv 0.8-9 with R
version 1.7.1. i didn't know that there was an another gam version with
package library(gam). Someone can tell me the basics differences between
them? I look for an help page on google but i only find mgcv help
pages.
- I
so mgcv package is the one i need! indeed, i want integrated smoothness
selection and smooth interactions rather than stepwise selection. i have
a lot of predictor, and i use gam to select those who are efficient
and exclude others. (using p-value)
thanks a lot for those precious information.
Yves Magliulo wrote:
so mgcv package is the one i need! indeed, i want integrated smoothness
selection and smooth interactions rather than stepwise selection. i have
a lot of predictor, and i use gam to select those who are efficient
and exclude others. (using p-value)
It is interesting that you
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
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
-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
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