On Thursday 13 December 2007, Frank E Harrell Jr wrote: > Andrew Park wrote: > > Hi there > > > > In rpart, one can get a graph of R-squared (using rsq.rpart (fit)), in > > which the x axis is the number of splits, and which contains two lines - > > an "apparent" R squared and an Rsquared based on the x error. > > > > I would like to caclulate these R-squared values, but cannot work out > > from the output how it is done. Is there any way to access the values > > that underpin this graph? Alternatively, is there any way to calculate > > them from the summary data? > > > > Thanks in advance, > > > > Andy Park > > Beware. Yi in his JASA paper about generalized degrees of freedom > showed that to get an unbiased estimate of R^2 from recursive > partitioning you have to use the formula for adjusted R^2 with number of > parameters far exceeding the number of final splits. He showed how to > estimate the d.f. Recursive partitioning seems to result in simple > prediction models but this is mainly an illusion. > > Frank Harrell
Hi Frank and others, hapen to have a link / citation for that paper? thanks! -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341 ______________________________________________ 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.
