[R] need help on GAM
Get some question about the function gam. Suppose I have a semiparametric model, Y~x1+x2+s(z1). Using gam, how could I get the estimates for the parametric part and nonparametric part respectively? And another question: we could find the coefficients for both parametric term and nonparametric term, what do these coefficients for the nonparametric term stand for, the coefficients for the base functions? Thank you! Song Song Liu School of Statistics 313 FordH 224 Church St. SE Minneapolis,MN 55455 __ [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
Re: [R] need help on GAM
Please read the posting guide and do give sufficient details for your questions to be answered. On Tue, 12 Oct 2004, Liu Song wrote: Get some question about the function gam. There are at least two functions gam() available for R, but none in standard R. Which package are you talking about? This is covered in the R FAQ, BTW. Suppose I have a semiparametric model, Y~x1+x2+s(z1). Using gam, how could I get the estimates for the parametric part and nonparametric part respectively? What do you mean by those terms? In the gam() in package gam, s(z1) is split into a linear and non-linear part, but all the terms *are* parametric (a smoothing spline is a parametric function of its argument). And another question: we could find the coefficients for both parametric term and nonparametric term, what do these coefficients for the nonparametric term stand for, the coefficients for the base functions? By definition, non-parametric terms do not have parameters aka coefficients. I suggest you ask for local advice on the statistical background to your questions, which you do need to understand before getting to using them in R. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ [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
Re: [R] need help on GAM
Prof Brian Ripley ripley at stats.ox.ac.uk writes: : And another question: we could find the coefficients for both : parametric term and nonparametric term, what do these coefficients : for the nonparametric term stand for, the coefficients for the base : functions? : : By definition, non-parametric terms do not have parameters aka : coefficients. This is definitely a candidate for the fortunes package. __ [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
Re: [R] need help on GAM
Get some question about the function gam. Suppose I have a semiparametric model, Y~x1+x2+s(z1). Using gam, how could I get the estimates for the parametric part and nonparametric part respectively? For a gam object (called, b,say) fitted using the mgcv `gam' then coef(b) will extract the coefficients for both the strictly parametric and smooth components of the model, labelled appropriately. summary(b) is also helpful. Often it is most useful to extract estimates of the smooths evaluated at a specified set of covariate values by using the gam `predict' method with type=terms. And another question: we could find the coefficients for both parametric term and nonparametric term, what do these coefficients for the nonparametric term stand for, the coefficients for the base functions? For mgcv gam objects the coefficients of the smooths are indeed the coefficients of the basis functions of the smooths. 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
