similar to: Package: cluster -- plot.partition() change title: main=""

Hello everyone. I just started learning R for clustering analysis in my research project. I tried k-means method and PAM method, both of which were properly processed with my data. I have some questions about PAM graphical output. Suppose to do the commands shown below; pm<-pam(D, 6) plot(pm) I got two charts after prompted. In the first chart, 6 oval clusters are drawn together

I'm fairly new to the silhouette functionality in the cluster package, so apologize if I'm asking something naive. If I run the 'agnes(ruspini)' example from the silhouette section of the cluster package vignette, and assign colours to clusters, two clusters have what appear to be incorrect colours in the silhouette plot. library(cluster) data(ruspini) ar<- agnes(ruspini)

I don't know if there is some fault in compiling or a bug of the new R-1.7.0 version: cl.pam.2 <- pam(as.dist(1-cor(mel.data)),2) plot(cl.pam.2) perform a right partitioning and silhouette plot on the old R-1.6.2 instead "Error in clusplot.default(x$diss,...... ; x is not numeric" is the output on the new R-1.7.0. Same platform: RH8.0 i686. Some suggestions? A.S.

Dear R-Devel subscriber, first, let me express my thank to the R-Core team for the new release! I appreciate their efforts and time spent to enhance R. In accordance with the 'NEWS' file (see excerpt of it below), [... o Changed the environment tree to be rooted in an empty environment, available as emptyenv(). baseenv() has been modified to return an environment with emptyenv() as

Dear R-Devel subscriber, first, let me express my thank to the R-Core team for the new release! I appreciate their efforts and time spent to enhance R. In accordance with the 'NEWS' file (see excerpt of it below), [... o Changed the environment tree to be rooted in an empty environment, available as emptyenv(). baseenv() has been modified to return an environment with emptyenv() as

Dear R users, I am mailing you about the graphical output of silhouette (cluster package) From the example of silhouette in help(silhouette): > ar <- agnes(ruspini) > si3 <- silhouette(cutree(ar, k = 5), # k = 4 gave the same as pam() above + daisy(ruspini)) > plot(si3, nmax = 80, cex.names = 0.5) from which one may conclude that group 1 is composed by

Hello, In cluster analysis with cluster, how does one colour the silhouette plots ? For example in using pam. There seems to be some problem there. Everything else can be coloured. Thanks, A. Mani Member, Cal. Math. Soc

Hi dear all It's the first time for me to install a developmental version of R, I came across following errors, my system is DISTRIB_ID=Ubuntu DISTRIB_RELEASE=10.04 DISTRIB_CODENAME=lucid DISTRIB_DESCRIPTION="Ubuntu 10.04.1 LTS" I downloaded the dev version of R in cran R source, and downloaded the recommended packages by using wget as described in R manual, and run

Let me firstly thank the R Core Team for their tremendous efforts in providing R 1.8.0. My following comment should therefore be understood as an "fyi-only". I source compiled R 1.8.0 for windows with ATLAS (source compiled, too). Everything works fine and R is running flawlessly! However, running "make check" stops during processing "internet.R". I checked the

Dear R user, I am a biochemist/bioinformatician, at the moment working on protein clusterings by conformation similarity. I only started seriously working with R about a couple of months ago. I have been able so far to read my way through tutorials and set-up my hierarchical clusterings. My problem is that I cannot find a way to obtain information on the rooting of specific nodes, i.e. of

Dear R-List member, I have installed the new version of R on my PC (see system details below). I can start the RGui with http_proxy succesfully. However, I do encounter two problems: 1) After starting the Rgui the following error message is displayed (vertical dots represent omissions of output): R : Copyright 2003, The R Development Core Team Version 1.7.0 (2003-04-16) . . . . Error in

Hello, I have a large data set that has more columns than rows (sample data below). I am trying to perform a partitioning cluster analysis and then plot that using pca. I have tried using CLUSPLOT(), but that only allows for 'princomp' where I need 'prcomp' as I do not want to reduce my columns. Is there a way to edit the CLUSPLOT() code to use 'prcomp', please? #

try: library(foreign) read.ssd("J:\\QM\\Reports\\Sarthur\\SAS_Application\\SAS_Data_Sets","use") instead, hth, Merry Christmas, Bernhard -----Original Message----- From: Stephen Arthur [mailto:sarthur67 at yahoo.com] Sent: 20 December 2002 16:55 To: ripley at stats.ox.ac.uk; rossini at blindglobe.net Cc: r-help at stat.math.ethz.ch; stvjc at channing.harvard.edu Subject:

Hi list, When I was using 'silhouette' from the 'cluster' package to calculate clustering performances, R crashed. I traced the problem to the fact that my clustering labels only have 2's and 3's. when I replaced them with 1's and 2's, the problem was solved. Is the function purposely written in this way so when I have clustering labels, "2" and

Hello, I have a large data matrix (68x13112), each row corresponding to one observation (patients) and each column corresponding to the variables (points within an NMR spectrum). I would like to carry out some kind of clustering on these data to see how many clusters are there. I have tried the function clara() from the package cluster. If I use the matrix as is, I can perform the clara

Doing the normal build process [1] for a first time with a R 2.0.0 snapshot -- the Sep 21 version I uploaded to Debian's 'experimental' section two days ago, ended in failure. The package in question is cluster 1.9.6 which should be 2.0.0-ready. The (partial) log follows: ----------------------------------------------------------------------------- [...] g77 -mieee-fp -fPIC -g -O2

Dear all I'm trying to run a cluster analysis with R Here are the commands: mydata <- na.omit(matrix) # listwise deletion of missing mydata <- scale(matrix) # standardize variables fit <- kmeans(mydata, 8) # 8 cluster solution # get cluster means aggregate(mydata,by=list(fit$cluster),FUN=mean) # append cluster assignment mydata <- data.frame(mydata, fit$cluster)

Dear all, I am trying (without much success) to use the fuction 'silhouette'. Would anyone encountered that before (or would know where I am wrong ?) Please find below the R ouput. Thanks in advance, L. > s <- silhouette(ct, as.dist(metric)) Error in "[<-"(*tmp*, iC, "sil_width", value = s.i) : number of items to replace is not a multiple of replacement

Hi, I am using fanny and I have estrange results. I am wondering if someone out there can help me understand why this happens. First of all in most of my tries, it gives me a result in which each object has equal membership in all clusters. I have read that that means "the clustering is entirely fuzzy". Looking at the graphics it is really difficult to understand how objects with so

Dear R list, I do encounter the following problem by generating either a png-file (example below) or a jpeg-file: By employing 'box(which="outer")' a box is drawn, except for the right line. If I generate the plot without the 'box(which="outer")', a line at the bottom in the graphics file still appears. However, both plots are displayed correctly in the R