similar to: Question:shardsplot (package:klaR)

Dear All, Would you please tell me how to display the sample No. on the map ? ---Below commands don't display the sample No.(from 1 to 150).--- library(som) library(klaR) iris.som3 <- som(iris[,1:4], xdim = 14,ydim = 6) library(klaR); opar<- par(xpd = NA) shardsplot(iris.som3, data.or = iris,label = TRUE) legend(3.5,14.3, col = rainbow(3), xjust =0.5, yjust = 0,legend =

Hi all I am hoping this is just a minor problem, I am trying to implement a best subsets regression procedure on some ecological datasets using the regsubsets function in the leaps package. The dataset contains 43 predictor variables plus the response (logcount) all in a dataframe called environment. I am implementing it as follows: library(leaps)

Hello R-User I have a table as tab-delimited textfile (291 rows, 83 columns). The first row are labels and the first line the variable names. I used the following code several times with different similar tables and it always worked. But now: setClass("of") setAs("character", "of", function(from) as.ordered(from)) Classe82<-cclasses <-

Dear all, I am trying to do a n-fold cross-validation for a regularized discrimant function analysis using rda from the package klaR. However, I have problems to predict the groups from the test/validation sample. The exmaples of the R documantation and some online webpage also do not work. Does anybody know what I have done wrong? Here my code # I want to use the first 6 observations for

Sorry, I forgot to mention that I used the package "klaR". > > Dear all, I am trying to do a n-fold cross-validation for a > regularized discrimant function analysis using rda from the package > klaR. However, I have problems to predict the groups from the > test/validation sample. The exmaples of the R documantation and > some online webpage also do not work.

Hi, I'm trying to use "stepclass" to do a stepwise variable selection with method=lda. I keep getting this warning message, which shows up once for each variable added to the model during variable selection: Warning message: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar), data = data, grouping = grouping, I don't know how to interpret this warning. I

Hi, a colleague ran a stepwise discriminant analysis twice in a row and got different results, suggesting some "sochasticity" in the algorithms involved. I looked at her data and found that there was a lot of collinearity, so that I reckoned that maybe "stepclass" (klaR) cannot find a clear winner when trying to include a new variable and makes a random choice. Is that true?

Is there another way of doing the bindings so that the Windows share doesn't run on TCP/IP but will still work with SAMBA? If so, where in the docs should I be looking, and if not - maybe this should be something discussed by the SAMBA dev people.. Regards, Marc. Return-Path: <twunder@iwmail.com> Delivered-To: samba@lists.samba.org Received: from femail14.sdc1.sfba.home.com

I use Windows, R version 2.5.1 When I try to run stepclass (klaR) I get an error message/warning saying: 1: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar), data = data, grouping = grouping, ... Actually, I look 16 warnings of this type. Can anyone tell me what this means? Also, it returns only 2 out of the 79 variables as important, however these variables

Hi, I run R 2.10.1 under ubuntu 10.04 LTS (Lucid Lynx) and klaR version 0.6-4. I compute a model over a 2 classes dataset (composed of 700 examples). To that aim, I use the function NaiveBayes provided in the package klaR. When I then use the prediction function : predict(my_model, new_data). I get the following warning : "In FUN(1:747[[747L]], ...) : Numerical 0 probability with

hi everybody, i?ve a problem with rsync runnig. constellation: rsyncserver is cwrsync at win2k-machine (without cygwin-beta against long filename-problem), client is a linux-ubuntu box. log from the server: (i just change names with xxx, no special charakters) this error happens all the time again, /overflow: flags=0xba l1=240 l2=22

Sorry if this post should be long but I tried to give you a piece of my data to reproduce my error message using hetcor: Fehler in result$rho : $ operator is invalid for atomic vectors Zus?tzlich: Warning messages: 1: In polychor(x, y, ML = ML, std.err = std.err) : 1 row with zero marginal removed 2: In polychor(x, y, ML = ML, std.err = std.err) : the table has fewer than 2 rows Error in

I'm working on bring up a new mail server to replace our current one. Our current mail server is running dovecot 1.1.16, with postfix using mbox format. User inboxes are stored locally on the mail server and all other mail folders in users home directory under mail which is NFS mounted on the mail server. For our new mail server I'm looking to switch to the Maildir format. Some

Thanks, I think that's a useful way to look at it (though if I wanted to bikeshed I'd suggest the name "DoubleIndirect" as a bit more precise than "VeryIndirect"). An aspect of it that I'm still puzzling over is that my target runtime (at least in its current form) doesn't have a way to represent/process a "VeryIndirect" pointer. So I'd like to

I try tu use mob() with my data.frame ('data.frame': 288 obs. of 81 variables; factors, numerics and ordered factors) My response is a binary variable and I should use for modelling a logistic regression (family=binomial). I read in the "MOB" Vignette that I could use a formula like this if I would like to have only partitioning variables apart from the response.