similar to: Help with identify() points on a PAM clusplot

I am using some functions from package clusterSim to evaluate the best clusters layout. Here is the features vector I am using to cluater 12 signals: > alpha.vec [1] 0.8540039 0.8558350 0.8006592 0.8066406 0.8322754 0.8991699 0.8212891 [8] 0.8815918 0.9050293 0.9174194 0.8613281 0.8425293 In the following I pasted an excerpt of my program:

Dear people, I used clusplot to plot a partition result. The partition result was from pamk with a distance object as input. Then I applied cmdscale on the same distance object for coordinates to make another scatterplot. My problem is this: the coordinates from the cmdscale calculation, though with the same shape, were different in scale and rotation from the scatter plot yielded by clusplot.

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? #

Dear R folk: Perhaps I'm just dense today, but I am having trouble reproducing the principal components plotted and summarized by clusplot. Here is a brief example using the pluton dataset. clusplot reports that the first two principal components explain 99.7% of the variability. But this is not what princomp is reporting. I would greatly appreciate any advice. With best regards, -- Tom

I am a relative novice with R and am having some difficulty using 'clusplot' (package Cluster). I have performed PCA analysis (using vegan) on a large set of morphometric measurements and revealed up to 4 principal components. To examine the grouping of the data I have used PAM followed by clusplot to visualise the clusters. My problem is that I would like to see the clusters plotted on

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)

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.

Hi there, I want to do classify some 2-dimensional points into four clusters by pam() in the cluster package. However, I encountered some problems. 1. How can I change the "xlab" and "ylab" instead of the default "Component 1" and "Component 2"? When I put "xlab" option in the function, it always says "formal argument "xlab"

The following code in clusplot.default (package cluster) is in error: x1 <- cmdscale(x, k = 2, eig = TRUE) var.dec <- sum(x1$eig)/sum(diag(x1$x)) if (var.dec < 0) var.dec <- 0 if (var.dec > 1) var.dec <- 1 x1 <- x1$points x1 has components with names "points" and "eig", not "x", so

Ok, now we have the mapping of color names to color codes (see below) and conversion to rgb (something like Ben Bolker's function), but how to convert rgb to hsv? Thanks to Brian Ripley, Peter Dalgaard and Ben Bolker Details below Regards Jens etc/colors.big maps 455 names to rgb in S syntax etc/rgb.txt maps 657 names to rgb in C syntax, but unlike colors() it has mixed upper and

Hello I have data of body length and body weight of people of different skin colors. I tried to write a code to plot body length and body weight according to the skin colors. (Thanks for Petr's advice so far.) A loop is used but an error shows up in the following code. It says: unexpected '}' in "

Dear Friends, require(cluster) x <- rbind(cbind(rnorm(10, 0, 0.5), rnorm(10, 0, 0.5)), cbind(rnorm(15, 5, 0.5), rnorm(15, 5, 0.5))) plot(pp <- pam(x, 2), which.plots = 1) How can I extract the coordinates used in the plot? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology Postal Address: P.O.Box 400400, Charlottesville, VA 22904-4400

Shown below is most of the FORTRAN subroutine named HCLUST. My question concerns the DO loop labeled as '10'. What happened to its CONTINUE statement? I will assume that after FLAG(I)=.TRUE. is executed that control returns to DO 10 I=1,N. Am I correct? Dave ---------------------------- C Initializations C DO 10 I=1,N C We do not initialize MEMBR in order to be able to

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

Dear R-list members, I am using the cluster package and by the generation of plot.partition I ran into the problem that an alternative title overlaps the default title. > plot.partition(clara.14,which.plot=2,stand=TRUE, main="Silhouette plot of 14 clusters") The manual states that all optional arguments for clusplot.default may also be supplied to plot.partition(). Altering the

I try to perform a clustering using an existing dissimilarity matrix that I calculated using distance (analogue) I tried two different things. One of them worked and one not and I don`t understand why. Here the code: not working example library(cluster) library(analogue) iris2<-as.data.frame(iris) str(iris2) 'data.frame': 150 obs. of 5 variables: $ Sepal.Length: num 5.1 4.9 4.7

Sorry, I never use pam. In the help, you can see that pam require a dataframe OR a dissimilarity matrix. If diss=FALSE then "euclidean" was use.So, I interpret that a matrix of dissimilarity is generated automatically. Problems may be in your data. Indeed pam(ruspini, 4)$diss write a dissimilaty matrix while pam(MYdata,10)$diss wite NULL 2017-08-17 16:03 GMT+02:00 Sema Atasever

Hi, I'm mighty new to R. I'm using it on Windows. I'm trying to cluster using a distance matrix I created from the data on my own and called it D10.dist. I loaded the cluster package. Then tried the following command... > agnes("E:D10.dist", diss = TRUE, metric = "euclidean", stand = FALSE, > method = "average", par.method, keep.diss = n < 1000,

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

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