sirilkt <jankee2010 <at> hotmail.com> writes: > > Hi All, > > When we run the command : summary ( newmod<-gam(Dlq~ formula,family,,data) ) > > in R, the output would the effect of smoothness in R. > > As of now to calculate the probability I am following the below approach: > > 1) Run the plot of the GAM , interpret the curves > > 2) Re Run the Regression as a GLM after taking into account the non linear > terms in step1 > > 3) Calculate the probability from the coefficients obtained in step2, using > the appropriate link function > > But I came across a paper by SAS ( > http://support.sas.com/rnd/app/papers/gams.pdf ), Where the parameters > outputs are also given when the program is run. > > So I was wondering if we have something similar in R also? I tried hard but > could not find anything.
It's still not entirely clear what you want to do. What's wrong with library(gam) data(kyphosis) gg <- gam(Kyphosis ~ s(Age,3) + s(Start,3) + s(Number,3), data=kyphosis, family=binomial) predict(gg,type="response") ? See ?predict.gam for more details. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.