Thank you very much. I am using gam() from mgcv actually. You answered my question about degree of freedom.
One more question, if I were to compare the results from gam() and glm(), which numbers are of the greatest interest? What if my response variables are binary? Thanks! -Janice -----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 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 are using gam() from package gam, in which case you probably need to look at the help file for step.gam. By default gam() in package mgcv estimates the appropriate degrees of freedom automatically as part of model estimation using generalized cross validation, (although there is an adjustable upper limit on the range of degrees of freedom considered). Package gss also has routines for fitting GAMs where the choise of df is fully automatic. best, Simon _____________________________________________________________________ > Simon Wood [EMAIL PROTECTED] www.stats.gla.ac.uk/~simon/ >> Department of Statistics, University of Glasgow, Glasgow, G12 8QQ >>> Direct telephone: (0)141 330 4530 Fax: (0)141 330 4814 ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
