Many thanks for your answer and the code that you offered me. I get this error message after calling mob (look at my given example). I guess it has something to do with the missings?
The iris example works also fine for me. Sorry that I am not enough into statistics to really understand the following: Achim Zeileis wrote: > > > ..... > For the variables for which a linear specification makes sense (at least > in each component) then you should include them for modeling. And those > variables for which it is not clear a priori what a useful parametric > specification would be should be used as partitioning variables. > ... > > What do you mean with "linear specification"? I would be very happy if you could explain. Thanks again B. Achim Zeileis wrote: > > On Wed, 13 Aug 2008, Birgitle wrote: > >> I try tu use mob() with my data.frame ('data.frame': 288 obs. of 81 >> variables; factors, numerics and ordered factors) >> My response is a binary variable and I should use for modelling a >> logistic >> regression (family=binomial). >> >> I read in the "MOB" Vignette that I could use a formula like this if I >> would >> like to have only partitioning variables apart from the response. >> >> Test.mob<-mob(Resp~1|Var1+Var2+...., data=dataframe, model=glinearModel, >> family=binomial()) > > This works for me. Considering an example that is easily reproducible: > classifying just two (out of three) species in the iris data. > > iris2 <- iris[-(1:50),] > iris2$Species <- factor(iris2$Species) > mb <- mob(Species ~ 1 | Petal.Length + Petal.Width + Sepal.Length + > Sepal.Width, data = iris2, model = glinearModel, family = binomial()) > > > > ----- The art of living is more like wrestling than dancing. (Marcus Aurelius) -- View this message in context: http://www.nabble.com/mob%28party%29-formula-question-tp18959898p18962866.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.