Martin, Sorry, I don't think I read your message carefully enough.
When you say the error message is "+", that woudl seem to indicate that you still had an unclosed parenthesis and that the function was looking for more input. Using a smaller data set (160 samples, 169 rows, only 5 classes) it did work fine for me. pa = presence/absence dataframe, opt.5$clustering = cluster IDs. ********************************************************************* > test <- tree(factor(opt.5$clustering)~pa) > test node), split, n, deviance, yval, (yprob) * denotes terminal node 1) root 160 371.000 3 ( 0.23750 0.08750 0.57500 0.07500 0.02500 ) 2) pa.symore < 0.5 79 216.500 1 ( 0.48101 0.17722 0.15190 0.13924 0.05063 ) 4) pa.artarb < 0.5 42 123.600 2 ( 0.07143 0.33333 0.26190 0.23810 0.09524 ) 8) pa.macgri < 0.5 31 75.280 2 ( 0.09677 0.45161 0.00000 0.32258 0.12903 ) . . . . . . . . . 3) pa.symore > 0.5 81 10.780 3 ( 0.00000 0.00000 0.98765 0.01235 0.00000 ) 6) pa.carrss < 0.5 11 6.702 3 ( 0.00000 0.00000 0.90909 0.09091 0.00000 ) * 7) pa.carrss > 0.5 70 0.000 3 ( 0.00000 0.00000 1.00000 0.00000 0.00000 ) * ************************************************************************ I'll try agin with a larger dataset and see if it's a memory limitation. Dave Roberts Martin Wegmann wrote: > On Friday 23 September 2005 17:08, Dave Roberts wrote: > >>Martin, >> >> If the data are actually coded 0/1, the tree function would >>probably intepret them as integers and try a regression instead of a >>classification. If the dependent variable is called "var", try > > > thanks, but I think I provided too less informations. > My dependent variable are the locations which are names (I could transform > them to numbers from 1 - n). The independent variables consist of 0/1 data > (species). > If I do > tree(locations~factor(species1)+factor(species2)+.....+factor(speciesn), > sp_data) > I receive the same results as without the factor() part. > BTW just a subset of the locations are displayed what is pretty weird > considering that I included all locations in the analysis. > > Martin > > > >>x <- tree(factor(var)~species) >> >>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ >>David W. Roberts office 406-994-4548 >>Professor and Head FAX 406-994-3190 >>Department of Ecology email [EMAIL PROTECTED] >>Montana State University >>Bozeman, MT 59717-3460 >> >>Martin Wegmann wrote: >> >>>Dear R-user, >>> >>>I tried to generate classification / regression tree with a >>>absence/presence matrix of species (400) in different locations (50) to >>>visualise species which are important for splitting up two locations. >>>Rpart and tree did not work for more than 10 species which is logical due >>>to the limited amount of locations (n=50). However the error prompt is a >>>"+" and no specific message, but I am pretty sure that I did not enter a >>>false sign by mistake. >>>Is it allowed at all to use 0/1 data for this statistical technique and >>>if yes is there a way or different method to use all 400 species entries? >>>Otherwise I would apply a PCA beforehand but I would prefer to have the >>>raw species informations. >>> >>>using R 2.1.1-1 (debian repos.) >>> >>>regards, Martin >> >>______________________________________________ >>R-help@stat.math.ethz.ch mailing list >>https://stat.ethz.ch/mailman/listinfo/r-help >>PLEASE do read the posting guide! >>http://www.R-project.org/posting-guide.html > > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html