Hi All, I have to say upfront that I am a complete neophyte when it comes to programming. Nevertheless I enjoy the challenge of using R because of its incredible statistical resources.
My problem is this .........I am running a regression tree analysis using "rpart" and I need to run the calculation repeatedly (say n=50 times) to obtain a distribution of results from which I will pick the median one to represent the most parsimonious tree size. Unfortunately rpart does not contain this ability so it will have to be coded for. Could anyone help me with this? I have provided the code (and relevant output) for the analysis I am running. I need to run it n=50 times and from each output pick the appropriate tree size and post it to a datafile where I can then look at the frequency distribution of tree sizes. Here is the code and output from a single run > fit1 <- rpart(CHAB~.,data=chabun, method="anova", control=rpart.control(minsplit=10, cp=0.01, xval=10)) > printcp(fit1) Regression tree: rpart(formula = CHAB ~ ., data = chabun, method = "anova", control = rpart.control(minsplit = 10, cp = 0.01, xval = 10)) Variables actually used in tree construction: [1] EXP LAT POC RUG Root node error: 35904/33 = 1088 n= 33 CP nsplit rel error xerror xstd 1 0.539806 0 1.00000 1.0337 0.41238 2 0.050516 1 0.46019 1.2149 0.38787 3 0.016788 2 0.40968 1.2719 0.41280 4 0.010221 3 0.39289 1.1852 0.38300 5 0.010000 4 0.38267 1.1740 0.38333 Each time I re-run the model I will get a slightly different output. I want to extract the nsplit number corresponding to the lowest xerror for each run of the model (in this case it is for nsplit = 0) over 50 runs and then look at the distribution of nsplits after 50 runs. Any help appreciated. Andy -- Andrew Halford Associate Researcher Marine Laboratory University of Guam Ph: +1 671 734 2948 [[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.