Let me remind you that originally you did not understand why the fitted values did not match up with some other set of values of var1 to var4 you cbind-ed. You need to predict at those values for what *you* did not to be `strange'.
Please do as I suggested and consult the documentation. On Thu, 7 Aug 2003, orkun wrote: > Prof Brian Ripley wrote: > > >On Thu, 7 Aug 2003, orkun wrote: > > > >[quoting me without attribution] > > > > > > > >>>Those are not predicted values, they are fitted values. Try predicting on > >>>the same set of variables as you printed. > >>> > >>> > > > >Precisely! From ?predict.glm > > > > newdata: optionally, a new data frame from which to make the > > predictions. If omitted, the fitted linear predictors are > > used. > > > >[...] > > > > > > > >>If predict(glm.obj,type="resp") does not give predicted vals, How can I > >>get predicted values ? > >> > >> > > > >Try reading the help page? It is quite explicit, and has examples, as do > >all good books on S/R. > > > > > > > I tried this: > #I think since an interaction exists in glm.obj, data.frame.obj did not > not work > #instead I used model.frame obj (it works) > newdata<-model.frame(glm.obj) > pr<-predict.glm(glm.obj,newdata,type="resp") > it works but there was a warning message: > prediction from a rank deficient fit may be misleading in predic.lm (....) > > any suggestions ? Follow advice when it is given to you. -- 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, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
