search for: cclust

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...

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 err...

...it 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] package On Wed, 5 Mar 2003, Igor Oleinik wrote: > 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 de...

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 clustIndex is calculated only for binary data, but, in turn, I can't find a way to specify either with the...

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 -0.769839 0.888365 1.178828 4 -0.333035 0.732639 0.802276 5 -0...

There is a new version of the 'CCLUST' package ,where i removed the extra command for the kmeans algorithm in the .R programm and also the comments about it in the .Rd help page. Now in the cclust library the kmeans algorithm can be applied only by using the cclust function. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-...

There is a new version of the 'CCLUST' package ,where i removed the extra command for the kmeans algorithm in the .R programm and also the comments about it in the .Rd help page. Now in the cclust library the kmeans algorithm can be applied only by using the cclust function. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-...

...t step is to determinate the number of clusters, that's why I 'm using ...snip... >... number of clusters. > A function is already implemented in R to calculate this index : > > clustIndex(cl,x, index="calinski") Where is that from? It's not part of R -- package cclust, perhaps? > where cl is the result of a clustering method , for instance: > > cclust(x,k,itermax,verbose=TRUE,method="kmeans") > > My probleme is that I can't calculate the Calinski's index when a cluster > contains only one datapoint : > > Error in c...

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 .....

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="manhatt...

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' Please help. Regards, Erik [[alternative HTML version deleted]]

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 --------------------------------...

...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 purpose criterion for answering the question whether the data is "quite homogeneous" or has two or more clusters. Even for one dimension data. However, in "cclust" a "clustIndex&quot...

...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". x<-rbind(matrix(rnorm(100,sd=0.3),ncol=2), matrix(rnorm(100,mean=1,sd=0.3),ncol=2)) cl<-cclust(x,2,20,verbose=TRUE,method="kmeans") Error: couldn't find function "cclust" plot(cl,x) Error: Object "cl" not found This happened with all contributed pa...

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 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-....

...29 69815 69933 70760 71340 75921 83972 90134 91061 . . . is it possible to cluster this data since it is in a single column ? I have used the following R commands: data <- read.table("cluster.txt") dataMatrix <- t(data) I then tried to cluster using the following: xcl <-cclust(dataMatrix,2,20,verbose=TRUE,method="kmeans") when I run this i receive the following error message: Error in x[rank(runif(xrows))[1:ncenters], ] : incorrect number of dimensions I would be grateful for any pointers in the right direction Thanks for your help Saurabh...

...0.448 0.204 ... This breaks: > cov(x) [,1] [1,] 0.9600812 > cov(x[20:30]) Erreur dans cov(x[20:30]) : fournir 'x' et 'y' ou bien 'x' en matrice And this behavior is braking function clustIndex (when used with unidimensional data), from the package cclust, file Rindexes.R, lines 137-147: ttww <- function(x, clsize, cluster) { n <- sum(clsize) k <- length(clsize) w<-0 tt <- cov(x)*n for (l in 1:k) w<- w+cov(x[cluster==l,])*clsize[l] zttw <- list(tt=tt, w=w)...

...ission from: (NULL) (198.203.181.181) When using barchart in the flexcust package, setting mcol=NULL to avoid the lollipops causes an error. Each panel shows the text message "Error using packet n replacement has length zero." where n is the panel number. > data(iris) > cl <- cclust(iris[,-5], k=3) > barplot(cl, mcol=NULL) #works fine > barchart(cl, mcol=NULL) # oops FWIW, as the data of the clusters is scaled showing the colMeans for the centers is misleading. The global mean of each column is 0, not the colMean of the centers.

...;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 , for instance: cclust(x,k,itermax,verbose=TRUE,method="kmeans") My probleme is that I can't calculate the Calinski's index when a cluster contains only one datapoint : Error in cov(x[cluster == l, ]) : supply both x and y or a matrix-like x Is there a way to solve this? thanx for your help, Davi...

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