similar to: How to use 'prcomp' with CLUSPLOT?

I'm clustering using kmeans, and it doesn't accept NA. if NA occurs in a column of the data frame, it occurs in every column, including column 1. they say that a (good) programmer can write FORTRAN in any language, so I came up with this, where tbl is the data frame containing NA - > newtbl<-NULL > for (i in 1:length(tbl)){if (!is.na(tbl[1,i])){ + newtbl<-if

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.

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 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

I created a clusplot from PAM results. It represents how signals have been classified. Signals are identified by a numerical label. My trial distance matrix is made up of 10 rows, one for eacjh signal. I assigned the signals iidentifiers as rownames of the distance matrix. rwn [1] "1104" "1332" "2057" "2425" "2483" "2530"

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"

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

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

I have my data in a table table <- table(test2$Filename, test2$PREDICT) I need to convert this table so it keeps the same structure, but is a different format. The current output is count data by Filename and I want to get the max for each Filename. Columns are: Filename, 1, 2, 3, 4, 5, 6, 7 When I try to convert it to a data.frame it reverts to Var1(Filename), Var2(1:7), Freq. My end goal

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

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 compiled R 2.1.0 under Windows XP SP2 as a preliminary to rebuilding a custom package for use with R 2.1.0. The compile completed successfully, and I was able to run demo(graphics) successfully. But make check and make check-recommended fail. > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 1.0 year 2005

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

First thanks to the fast answer regarding the "Clustplot problem"... Regarding a new problem: for (i in 1:5) { z <- clara(adata, i) plot(z) } in the above code in the plot screen I get something like: clusplot(clara(x=adata,i)) in title in the 2nd type of plot I get silhouete plot of clara(x=adata,k=i,samples=50) How can I pass the real value to

Hi there, Sorry for the double email. Does R have the packages for the following clustering methods? And if it does, what the commands for them? 1. SOM (Self-organization map) 2. Graph partitioning: 3. Neural network 4. Probability Binning Thank you very much! Linda [[alternative HTML version deleted]]

Dear R Users, It works fine. while i read the dataset from the text file. (refered R-data import -export*.pdf) > read.table("c:\\DataES.txt") V1 V2 1 ACW261 33 2 ACW311 7 3 ACW321 31 4 ACW342 39 5 6 7 Now my question is how do i /*convert text file Data into *.RData* which i can use as a dataset/data.matrix whereby i can use it for clusplot. Thanks in Advance, JJ ---

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