The Gls function in the rms package is a frontend to gls that allows you to use all the graphics and other methods available in rms. Frank
SamiC wrote: > > Hi, I am trying to plot the original data with the line of the model using > the predict function. I want to add SE to the graph, but not sure how to > get them out as the predict function for gls does not appear to allow for > SE=TRUE argument. > > Here is my code so far: > > f1<-formula(MaxNASC40_50~hu3+flcmax+TidalFlag) > > vf1Exp<-varExp(form=~hu3) > > B1D<-gls(f1,correlation=corGaus(form=Lat~Lon, nugget=TRUE),weights=vf1Exp > , data=ocean) > > ochu3<-seq(from=2.9,to=4,length=120) > ocflc<-seq(from=0,to=0.8,length=120) > tidal1<-rep(c("1"),length=120) > > mydata1<-data.frame(TidalFlag=factor(tidal1),hu3=ochu3,flcmax=ocflc) > lineNASC1<-predict(B1D,newdata=mydata1,type="response") > lineNASC1<-as.data.frame(lineNASC1) > > plot(ocean$MaxNASC40_50[ocean$TidalFlag==1]~ocean$flcmax[ocean$TidalFlag==1) > lines(lineNASC1$lineNASC1~mydata1$flcmax) > > Tidal Flag is a factor (so i assume i have to plot seperate graphs for > each level). > > When I have tried to use the effects package I get the error: Error in > x$formula : object of type 'symbol' is not subsettable. > > Also when i have been trying to predict values from a zero inflated > negative binomial, I am getting the same line of fit regardless of what is > on my X axis (depsite different variables have positive and negative > relationships). > > any imput on any of these problems would be appreciated. > > Thanks > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/GLS-Plotting-Graphs-with-95-conf-interval-tp3659814p3660953.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.