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Dear R fans, I have got a difficult sounding problem. For fitting a linear model using continuous response and then for re-fitting the model after excluding every single variable, the following functions can be used. library(MASS) model = lm(perf ~ syct + mmin + mmax + cach + chmin + chmax, data = cpus) dropterm(model, test = "F") But I am not sure whether any similar functions is available in R for multivariate data with categorical response. My data looks like the following: mat <- matrix(rnorm(700), ncol=5, dimnames=list( paste("f", c(1:140), sep...

Dear R user, I used from the library MASS the dataset cpus and the skript plot.tree.sequence.R, which are included in the tree package: >library(MASS) > data(cpus) > cpus.ltr <- tree(log10(perf) ~ syct + mmin + mmax + cach >+ + chmin + chmax, data=cpus) At home it works but at work I get this message: >Error in .C("BDRgrow1", as.double(X), as.double(unclass(Y)), as.double(w), : C/Fortran function name not in load table I do not understand this message and I would be very glad if someone could give me some advic...

...1, 163, 166, 167, 169, 170, 173, 174, 175, 176, 177, 183, 184, 187, 188, 189, 194, 195, 196, 197, 198, 199, 202, 204, 205, 206, 208, 209) cpus2 <- cpus[, 2:8] # excludes names, authors? predictions attach(cpus2) cpus3 <- data.frame(syct = syct-2, mmin = mmin-3, mmax = mmax-4, cach=cach/256,chmin=chmin/100, chmax=chmax/100, perf) detach() CVnn.cpus <- function(formula, data = cpus3[cpus.samp, ], maxSize = 10, decayRange = c(0,0.2), nreps = 5, nifold = 10, alpha= 9/10, linout = TRUE, skip = TRUE, maxit = 1000,...){ #nreps=number of attempts to fit a nnet model with randomly ch...

Hello, Can anyone offer any insight on graphing classification dendrograms with the nodes marked? plot(tree()) produces a nice tree structure but there's no acccompanying text. Thanks, D S. David White sdavidwhite at bigfoot.com Columbus, Ohio -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read