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Dear R users, I want to do discriminant analysis on my data. I have successfully followed the discriminant analysis in V & R on the iris data: > ir <- rbind (iris3[,,1],iris3[,,2],iris3[,,3]) > ir.species <- c(rep("s",50),rep("c",50),rep("v",50)) > a <- lda(log(ir),ir.species) > a$svd^2/sum(a$svd^2) [1] 0.996498601 0.003501399 > a.x <-

Dear R users, I am a novice user working through V & R. My first question stems from p20 of the second edition.: I perform the following actions: > mydata <- c(2.9,3.4,3.4,3.7,3.7,2.8,2.8,2.5,2.4,2.4) > names(mydata) <- c('c','j','b','e','i','h','g','d','f','a') > mydata c j b e i h

Dear r-help, I am trying to build a new function (to process rpart objects) that will output matrix that has a row for each node and a column for each feature. With each entry in the table is a numerical property at that node for that feature (e.g. surrogate split agreement, improvement). My current trouble is that the only clue to the identity of the feature is stored as the *name* of the

Dear All, I was trying to follow some of the examples in Venables and Ripley "Modern applied ... with S-plus" I have downloaded a copy of the iris data set and loaded into R. : however I cannot use the apply command (from p47): > apply (iris, 2 ,mean) Error in sum(..., na.rm = na.rm) : invalid "mode" of argument > apply (iris, c(2) ,mean) Error in sum(..., na.rm =

Hello All, I would like to use R for k-NN (nearest neighbor) clustering for pattern recognition. However, I don't see it. I don't think 'hclust' or 'kmeans' are what I am looking for. Thanks for your help, Clayton Springer -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Do those who have had trouble finding stuff in the R-archive used the search engine? http://www.scirus.com/ And as far as threading goes. My mailler "mutt" threads the mailing list quite nicely. --Clayton -- Clayton Springer, Ph. D. Sandia National Laboratories csprin at ca.sandia.gov Biosystems Research Department (925) 294-2143 P.O. Box

Dear r-help, I am looking for additional documentation on the "adj" column in rpart's splits matrix. The help says: adj gives the adjusted concordance for surrogate splits I am looking info about "adjusted concordance". I cannot find this phrase in either Therneau & Atkinson original RPART documentation or the CART book. This question came up in the

Dear r-help, I am having an intermittant error using R on a linux beowulf cluster. I am using my homebrew script to test the performance of various feature subsets with "lda". ------------- The general procedure is as follows: I load the data from an .Rdata file (which has generated by R-1.3.0) run my script "Iterate()" ... At a different iteration each time I get the

Hi All, When I tried to do logistic regression and I got the following messages: > SampledW.glm.ALL <- glm (V1 ~ ., family = binomial, data = SampledW) Warning messages: 1: Algorithm did not converge in: (if (is.empty.model(mt)) glm.fit.null else glm.fit)(x = X, y = Y, 2: fitted probabilities numerically 0 or 1 occurred in: (if (is.empty.model(mt)) glm.fit.null else glm.fit)(x = X, y =

Dear R developers, I am newbie to R-development. I have written mutated the rpart to obtain myown package that performs some additional calculations on trees. I have altered the names of rpart's functions so there is no namespace conflict, but there is redunant functionality. However there some remaining functions that I am not sure what to do with. When I run R and load both libraries I

Dear r-help, Is there any available description of the components of lqs objects found in the package "lqs"? > names(slts) [1] "crit" "sing" "coefficients" "bestone" [5] "fitted.values" "residuals" "scale" "terms" [9] "call"

Dear r-devel, I am mutating rpart to do calculations on trees. I am trying to extract information from the tree. However, I got a seg. fault. This is the offending line in "rpmatrix.c": deltaI[0][0] = spl->improve; (Commenting it out cures the seg fault) I would like some advice on how to debug this. I have allocated memory with calloc and deltaI[0][0] should be

Dear R folks, Thanks to all your help before I have loaded a 1-D toy data set into R and did LDA on it. The toy data has Class=0 if value>0. > XY <-- read.table ("test.xy",header=T ) > XY X.Class value 1 0 60.4897262 2 0 32.9554489 3 -1 -53.6459189 4 0 44.4450579 . . . 998 -1 -43.4183157 999 0