similar to: Cluster prediction from factor/numeric datasets

Hi all, I am interested in performing a cluster analysis on ecological data from forests in Pennsylvania. I would like to develop definitions for forest types (red maple forests, upland oak forests, etc.(AH AR in attached table)) based on measured attributes in each forest type. To do this, I would like to 'draw clusters' around forest types based on information from various tree

Hi - Writing to see if someone can suggest whether a problem warrants a bug report. It concerns the use of stepFlexclust in the flexclust package. The problem concerns the size of clusters returned. Versions: R-2.7.0 on Windows XP; RODBC_1.2-3 code snippet: r8 <- stepFlexclust(df,8,nrep=100,FUN=kcca, family=kccaFamily("kmedians")) summary(r8) ## returns cluster sizes of 51, 115,

Sorry, to bother the list one more time: but the following worked at least for 'urca': in NAMESPACE I now included explicitly: import(methods) a fix of the 'urca'-package will be uploaded to CRAN on the weekend. Fritz, will this work for ypur package 'flexclust' too? I have in my DESCRIPTION imports: methods and in flexclust it is in depends: methods. However, both

Dear R-Devel subscriber, as a follow up to my yesterday's email: I tested an analogous example with the S4-package "flexclust" by executing the following code: library(flexclust) example(cclust) cl After saving the work space and starting a new R process with the restored work space, the same behaviour (i.e., the methods pertinent to "flexclust" are not used, even after

Full_Name: Chris Hane Version: 2.10.1 OS: Windows Submission 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,

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 everybody, I''m using R on a 64-bit Ubuntu 9.04 (Jaunty). I prefer to install R packages from source, even if they are available in Synaptic. The problem is that I can''t install/compile kernlab. Everything works fine until it gets to the lazy loading part: ** preparing package for lazy loading Creating a new generic function for "terms" in "kernlab"

A new version of kernlab has just been released. kernlab is a kernel-based Machine Learning package for R. kernlab includes the following functions: o ksvm() : Support Vector Machines for classification, regression, novelty detection, native multi-class classification, support for class-probability output and confidence intervals in regression. o gausspr()

A new version of kernlab has just been released. kernlab is a kernel-based Machine Learning package for R. kernlab includes the following functions: o ksvm() : Support Vector Machines for classification, regression, novelty detection, native multi-class classification, support for class-probability output and confidence intervals in regression. o gausspr()

Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working

It seems that many package authors do not proofread the help installed with their packages. The Rd converter is not a parser, and it will silently produce incorrect results on incorrect input (and some correct input). Here are a few hints about some common errors: 1) When you run R CMD check you get a PDF manual at <pkg>.Rcheck/<pkg>-manual.pdf. Read through it looking for

Hi, I am new to bioconductor, trying to install KEGGSOAP package, but got warnings() when installing and error message when trying to load the package, can anyone suggest what went wrong? many thanks John > source("http://bioconductor.org/biocLite.R") Bioconductor version 2.11 (BiocInstaller 1.8.3), ?biocLite for help > biocLite("KEGGSOAP") BioC_mirror:

I haven't read the book, but could anyone explain more about this parameter? help(agnes) says that ac measures the amount of clustering structure found. From the definition given in help(agnes.object), however, it seems that as long as the dissimilarity of the merger in the final step of the algorithm is large enough, the ac value will be close to 1. So what does ac really mean? Thank

Hi, I'm clustering objects defined by categorical variables with a hierarchical algorithm - average linkage. My distance matrix (general dissimilarity coefficient) includes several distances with exactly the same values. As I see, a standard agglomerative procedure ignores this problems, simply selecting, above equal distances, the one that comes first. For this reason the analysis in output

Hello, Does anyone knows how to do the plots from discriminant analysis (lda and qda)? Is there any computed function to do the stepwise procedure? thank you in advance Marta

Hello, In the documentation for agnes in the package 'cluster', it says that NAs are allowed, and sure enough it works for a small example like : > m <- matrix(c( 1, 1, 1, 2, 1, NA, 1, 1, 1, 2, 2, 2), nrow = 3, byrow = TRUE) > agnes(m) Call: agnes(x = m) Agglomerative coefficient: 0.1614168 Order of objects: [1] 1 2 3 Height (summary): Min. 1st Qu. Median Mean 3rd

-----Original Message----- From: Dariusz Krempa [mailto:imperiaonline4@gmail.com] Sent: Wednesday, September 19, 2012 11:23 AM To: Marc Tousignant Subject: Re: [Xen-users] PCIe/VGA passthrough 2012/9/19 Marc Tousignant <myrdhn@gmail.com>: > > > -----Original Message----- > From: Dariusz Krempa [mailto:imperiaonline4@gmail.com] > Sent: Wednesday, September 19, 2012 9:29 AM

I'm clustering rather large data sets and would like to cut the dendrograms to get a better view of specific components. I calculate the dissimilarity matrix using daisy() because I have a mixture of variable types: factors, ordered factors and numerical variables. If I want one dendrogram, I use agnes() for the agglomerative nesting and pltree() to draw the dendrogram. That way, I get the

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]