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Hello, I faced something I can't understand. When I use boxplot.stats(1:10) and quantiles(1:10) the results are different for 25% and 75%: > boxplot.stats(1:10) $stats [1] 1.0 3.0 5.5 8.0 10.0 > quantile(1:10) 0% 25% 50% 75% 100% 1.00 3.25 5.50 7.75 10.00 Actually, I expected the value 3 for 25% and 8 for 75% as results of quantile(1:10). Can you please explain me

Hello, When I plot or look at the error rate vector for a random forest (rf$err.rate) it looks like a descending function except for a few first points of the vector with error rates values lower(sometimes much lower) than the general level of error rates for a forest with such number of trees when the error rates stop descending. Does it mean that there is a tree(s) (that is built the first in

...i is the geometric mean of A[i] and A[i+1], Bi=SQRT( A[i] * A[i+1] ): Suppose, I select Bk as an optimal parameter. Which Ai does this optimal Bk correspond to? Which of the two ways should I follow? Are there any other ways of choosing a right-sized tree? Does anybody have any ideas? Thank you Kutinsky Vladimir -------------- next part -------------- An HTML attachment was scrubbed... URL: https://stat.ethz.ch/pipermail/r-help/attachments/20010609/a181e4b0/attachment.html

Hi! I faced a few problems with configuring ESS. I sent my questions to the ESS mailing list but recieved no replies, so i'm sending them here in hope someone will help me. I've just installed ESS and I'm quite a novice at it. In the docs it is said that setting "ess-insert-function-templates" to non-nil value will result in the edit buffer containing a skeleton function