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...ludes fixed d.f. and free d.f. terms) @@ -1247,7 +1250,7 @@ null.deviance = nulldev, iter = iter, weights = wt, prior.weights = weights, #df.residual = resdf, df.null = nulldf, y = y, converged = conv,sig2=G$sig2,edf=G$edf, - boundary = boundary,sp = G$sp,df=G$df,nsdf=G$nsdf,Vp=G$Vp,mgcv.conv=G$conv,gcv.ubre=G$gcv.ubre) + boundary = boundary,sp = G$sp,df=G$df,nsdf=G$nsdf,Vp=G$Vp,mgcv.conv=G$conv,gcv.ubre=G$gcv.ubre, hat=G$hat) } diff -ur c:/usr/temp/work/mgcv/src/mgcv.c ./src/mgcv.c --- c:/usr/temp/work/mgcv/src/mgcv.c 2002-05-17 02:51:22.000000000 +...

Dear Simon, Thank you for your quick reply! I used to perform the GAMsetup in the following manner: GAMsetup sintax: x.summer: vector used for construct the spline knots<-14 N<-length(x.summer) x<-array(x.summer,dim=c(1,N)) G<-list(m=1,n=N,nsdf=0,df=knots+1,dim=1,s.type=0,by=0,by.exists=FALSE,p.order=0,x=x,n.knots=knots,fit.method="mgcv") H<-GAMsetup(G) with the new version mgcv 1.4.1 gam.setup this does no longer work and gives me the following error: Error in gam.setup(G) : First argument is no sort of formula! What is...

Dear R users, Using the library(mgcv) and running R under MacOSX, I have fitted a generalised additive model with binomial errors in order to check the linearity of two continuous variables ap2mm and diffdaysm in a glm: > mymodel.gam <- gam(diedhos~ s(ap2mm) + Dweekm + s(diffdaysm) + Dweekm:diffdaysm + ap2mm:Dweekm, binomial) I would like postscript gam plots for the two smoothed

...ut the entire model object is needed as input. I looked into it further, and the predict method (using type='lpmatrix") depends on the following model components: object$model object$terms object$coefficients object$contrasts object$xlevels object$pterms object$nsdf object$smooth object$Xcentre Stripping out the other object parts saves some space, but the "smooth" part seems to still be storing all the original data. Isn't there some way that I can just use the coefficients? Thanks, Gene [[alternative HTML version deleted]]