similar to: estimating number of clusters ("Null or more")

> Well, that is in all good texts on R, together with the > solution: drop=FALSE. See ?"[" for the on-line details. OK. Thank you a lot. Now patched cclust and clustIndex work fine for 1D case. BTW, why not to apply the "drop=F" to these functions? I guess other users need 1D case as well. kind regards, Valery A.Khamenya

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

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

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 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, 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

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

Hi all, Why subscripting a one column matrix drops one dimension? > x<- matrix(rnorm(100), ncol=1) > str(x) num [1:100, 1] -0.413 -0.845 -1.625 -1.393 0.507 ... > str(x[20:30,]) num [1:11] -0.315 -0.693 -0.771 0.448 0.204 ... > str(x[20:30]) num [1:11] -0.315 -0.693 -0.771 0.448 0.204 ... This breaks: > cov(x) [,1] [1,] 0.9600812 >

Dear Christian, first of all thank you for your answer. I am going to parse through the pages you told me. Meanwhile I'd like to note that probably it is a good idea to put 2-3 lines of R-code demonstrating such a simple needs somnewhere in docs of `cluster' package. E.g. x<-rnorm(500) ... # output means we have rather 1 claster x<-c(rnorm(500), rnorm(500)+5)

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 ,

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),

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]

> > It would be nice not only for me. > > I agree totally. If you belong to R-contributors group then thanks a lot in advance! > The problem is that you have to formalize what a cluster is, > and this is not a well defined notion. > It has different meanings in different applications. you are right if one follows the idea of full formalization of the notion it

Hi All: Package TSERIES is stated to depend on MVA. However, there is no MVA package to be found under the list of package sources. Best wishes, ANDREW tseries: Package for time series analysis Package for time series analysis with emphasis on non-linear and non-stationary modelling Version: 0.7-6 Depends: ts, mva, quadprog Date: 2001-08-27 Author: Compiled by Adrian

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 list, not really a problem to solve but a strange unwanted behavior (at least I do not like it): I'm loading library(multiv) to use sammon. Later I load library(MASS) which tells me that sammon is masked now, because there is also a MASS version of sammon. Since I believe that the MASS version is at least as good as the multiv version, I would also use the MASS version, but help(sammon)

Hello, I'm playing around with cluster analysis, and am looking for methods to select the number of clusters. I am aware of methods based on a 'pseudo F' or a 'pseudo T^2'. Are there packages in R that will generate these statistics, and/or other statistics to aid in cluster number selection? Thanks, John. --

> 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 ---------------------------------------------------------------------------

Hi all, is there any package in R capable of smooth approximation of CDF basing on given sample? (Thus, I am not speaking about ecdf) In particular, I expect very much that the approximation should subject to the property: f(x0)<=f(x1) for x0<x1, where x0 and x1 belong to range of the sample given. Polynomial approximation could be OK for me as well. P.S.