similar to: R-beta: "cclust" Package

Dear R users, When I run the following code, R crashes: require(cclust) x <- matrix(c(0,0,0,1.5,1,-1), ncol=2, byrow=TRUE) cclust(x, centers=x[2:3,], dist="manhattan", method="kmeans") While this works: cclust(x, centers=x[2:3,], dist="euclidean", method="kmeans") I'm posting this here because I am not sure if it is a bug. I've been searching

I would like to see an example of a data matrix for cclust and how to import it to cclust. In fact, i don't know how to give my imput for cclust program! i test this file 1 0.23 1.52 2 0.52 1.25 3 0.13 1.89 4 0.78 1.11 i do >library(cclust) >x<-scan("test.matrice.phyl") >cclust(x,2,method="kmeans") i have this error message: Error in sample(length(x),

To Whom It May Concern, I am currently trying to use R to perform a "kmeans" clustering of a three dimensional data set. In the directory R-1.5.1/library/cclust/data/ I have created a file that has the following format (only the first few lines are shown for brevity): B X.Vtl X.Vtu 1 -0.529043 1.307031 1.625169 2 -0.752502 1.132813 1.480548 3

I have checked that section already. Sorry, I should have mentioned that. Memory limit increase does not work. Installtion of msvcrt.dll does not work either. Thank you. -----Original Message----- From: ripley at stats.ox.ac.uk [mailto:ripley at stats.ox.ac.uk] Sent: Wednesday, March 05, 2003 2:44 PM To: Igor Oleinik Cc: r-help at stat.math.ethz.ch Subject: Re: [R] problem with cclust[er]

Hello, here is my problem, After looking at the mail archives, I found a description of the error I get when I use this package. At first I even tought that they were showing how to solve it. But the thing is that by saying "the programmer forgot drop=FALSE" doesn't show me how I should get rid of the problem I have looked inside the package very quickly and I found three

Hello, I am calling cclust function in cclust package repeatedly until some ceratain conditions for a cluster are met. Unfortunately, the system crashes on the second call (after debugging). # kmeans res1 is a well defined matrix cl <- cclust(res1, as.numeric(ncntrs), iter.max = 20, verbose = FALSE, dist="manhattan", method="kmeans") RGui has generated errors and will

Hi, I am using the following syntax to enter data and perform a cluster analysis: x <- read.table ("clstrdbt.csv", header=TRUE, sep = ",",fill = TRUE) cl<-cclust(x,4,20,verbose=TRUE,method="kmeans") This is the result I receive: Error in cclust(x, 4, 20, verbose = TRUE, method = "kmeans") : (list) object cannot be coerced to type 'double'

Hi, I'm trying to debug a function I wrote to calculate the cindex for a hierarchical tree. For this it is useful to compare my calculations with those in output from the clustindex function, in the cclust library. There's no way, however, to have the cindex value for a given output of the cclust function, as a NA value is always returned. This happens almost surely because the cindex in

hi, What is the significance of the 2nd arg in cclust, the 'number of clusters'. I have one matrix with two columns representing x,y coards. I'd like to see how random the distributions is. If I try cclust with 'number of clusters' 1 I get an error, > 1 works though. j. -- ...................... ..... Jason C. Leach .. Current PGP/GPG Key ID: 43AD2024

Dear all, I have recently installed R0.63.2. under Win95. and with it a number of contributed packages. The instructions for adding packages was to unzip the files into the "directory rw0632\library. They are then available for use." However, when I tried one of the function below, I got a Error: couldn't find function "cclust".

Hi all, I am wandering.. is it possible to cluster data which is in a single column ? for example.. I have some data as follows: 4013 7362 7585 9304 11879 14785 21795 30500 30669 30924 33988 36975 40422 42911 50501 51593 53729 54338 55497 57337 61993 62601 66229 69815 69933 70760 71340 75921 83972 90134 91061 . . . is it possible to cluster this data since it is in a single column ? I have

Hi R users! I have a bit of a problem with using an hierarchical clustering algorithm: a<-c(1:15) b<-rep(seq(1:3), 5) c<-rnorm(15, 0,1) d<-c(sample(1:100, 15, replace=T)) e<-c(sample(1:100, 15, replace=T)) f<-c(sample(1:100, 15, replace=T)) data<-data.frame(a,b,c,d,e,f) q<-data.frame(data$d, data$e, data$f) q<-scale(q) What i want to do is to use an

> Nothing to do with me: you should report problems with > packages to the > maintainers, rather than R-help or a member of R-core. OK. I've sent a note about cclust patch to Evgenia Dimitriadou Thank you for your valueable comments. (No more reply needed in this thread) kind regards, Valery A.Khamenya ---------------------------------------------------------------------------

I have to solve a clustering problem. My first step is to determinate the number of clusters, that's why I 'm using the Calinski index ( [tr(b)/(k-1)]/[tr(w)/(k-1)] ) which i try to maximize to have the best number of clusters. A function is already implemented in R to calculate this index : clustIndex(cl,x, index="calinski") where cl is the result of a clustering method ,

Hi All, For the function "bclust"(e1071), the argument "base.method" is explained as "must be the name of a partitioning cluster function returning a list with the same components as the return value of 'kmeans'. In my understanding, there are three partitioning cluster functions in R, which are "clara, pam, fanny". Then I check each of them to

Hi- I'd like to apply some of the cluter indices, using 'clustindex' in the cclust package, but using output from hierarchical clustering using 'hclust' in the mva package. The two packages use a different format for storing the results of clustering; has anyone coerced one into the other? Thanks! -John Barnett

Dear R Experts, I am running a cluter analysis using kmeans and have come across an error to which I am unable to find a solution. First, let me describe the problem: THE R CODE IS: -------------------------------------- # NRM is a 100 x 100 numerical matrix infile = 't:\\NRM\\NRM' groups = 7 outfile = 't:\\NRM\\cluster.groups' print( paste(infile, groups, outfile, sep='

Hi All, while looking why the cclust(cclust) doesn't work for 1-dimensional data, I've found unpleasant behavior in semantics of R. Indeed: is.matrix(matrix(cbind(c(1,2,3,4)),ncol=2)[1:2,]) == TRUE but: is.matrix(matrix(c(1,2))[1:2,]) == FALSE kind regards, Valery A.Khamenya --------------------------------------------------------------------------- Bioinformatics

Hello All, I'm having some trouble figuring out what the clearest way to plot my k-means clustering result on an my existing MDS. First I performed MDS on my distance matrix (note: I performed k-means on the MDS coordinates because applying a euclidean distance measure to my raw data would have been inappropriate) canto.MDS<-cmdscale(canto) I then figured out what would be my optimum

Hi all, once more about the old subj :-) My data has too much various distribution families and for every particular experiment I need just to decide whether the data is "quite homogeneous" or it has two or more clusters. I've revisited the following libraries: amap, clust, cclust, mclust, multiv, normix, survey. And I didn't find any ready-to-use general