From: Uwe Ligges <ligges_at_statistik.tu-dortmund.de <mailto:ligges_at_statistik.tu-dortmund.de?Subject=Re:%20[R]%20Help%20with%2 0gam> > Date: Wed, 11 May 2011 19:08:38 +0200
On 11.05.2011 17:22, Zsolt Macskasi wrote: > Hi, > <http://tolstoy.newcastle.edu.au/R/e14/help/11/05/1036.html#1040qlink1> > I am a brand new user of R and I am trying to use the gam procedure with the package mgcv. I did a bit of my homework by consulting the R-manual, as well as the mgcv manual written by Simon Wood. I admit it was just a few hours, but what I am trying to do is really basic. Essentially, what I am trying to do is to generate the fitted values after the execution of the gam procedure and export them into Excel. > > Here is my program: > > ABC<- read.table("Incidence Data.csv", header=TRUE, sep=",") probably the next three lines can be omitted if you just say: fit <- gam(incidence~te(age,birthyear), data=ABC, family=poisson, fit=TRUE) <http://tolstoy.newcastle.edu.au/R/e14/help/11/05/1036.html#1040qlink2> > incidence<- ABC[,1] > age<- ABC[,2] > birthyear<- ABC[,3] > fit<-gam(incidence~te(age,birthyear), family=poisson, fit=TRUE) > <http://tolstoy.newcastle.edu.au/R/e14/help/11/05/1036.html#1040qlink3> > All this works. Now, how can I see the fitted values and copy them back to Excel? As for most fitted models, you can get Fitted values: predict(fit) Coefficients: coef(fit) etc. Uwe Ligges <http://tolstoy.newcastle.edu.au/R/e14/help/11/05/1036.html#1040qlink4> > Thank you very much, > > Zsolt > > [[alternative HTML version deleted]] > Note that predict(fit) will give the additive fit. If you are looking for the fitted mean values, I would do the following: ds <- data.frame(fit$fitted.values) write.csv(ds, file = "test.csv") #to write the fitted mean values to a csv file Paula McGee [[alternative HTML version deleted]] ______________________________________________ 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.
