similar to: recursive function, how to avoid list structure in return value

Dear all, I would like to draw a dendrogram and mark some parts/branches (by using "segments") including their labels. If I draw it without specifying the length of x axix, I am able to do that (as in My dendrogram 1 of the following codes). However, if I want to specify the x axix, I am not able to draw marking line (by using "segments") including labels (as in My dendrogram

I would like to be able to exert certain types of control over the plotting of dendrograms (representing hierarchical clusterings) that I think is best achieved by modifying the dendrogram object prior to plotting. I am using the "dendrogram" class and associated methods. Define the cluster number of each cluster formed as the corresponding row of the merge object. So, if you are

Dear R-help community, I have had trouble in the past installing the latest version of R: we got the errors shown below (the computer specifications and version of R are below that). Does anybody have tips for compiling the latest version of R so that I can avoid these errors? configure make ... ... ... f90: CODE: 0 WORDS, DATA: 0 WORDS gcc -G -L/usr/local/lib -o stats.so init.o kmeans.o

This worked for me with your example: source("dumpdata.R") storage.mode(x.hc$merge) <- "integer" plot(x.hc) (R-1.4.1 compiled from source on WinNT4.) Andy > -----Original Message----- > From: Hugh Chipman [mailto:hachipma at icarus.math.uwaterloo.ca] > Sent: Wednesday, February 20, 2002 5:32 PM > To: andy_liaw at merck.com > Cc: r-help at stat.math.ethz.ch

Dear R-Help, I have a clustering problem with hclust that I hope someone can help me with. Consider the classic hclust example: hc <- hclust(dist(USArrests), "ave") plot(hc) I would like to cut the tree up in such a way so as to avoid small clusters, so that we get a minimum number of items in each cluster, and therefore avoid singletons. e.g. in this example, you can see

Hi,All.Sorry for the group mail. I recently met a question and I have struggled on that for a while but failed to found the solution. I have a distance matrix as below. --- 0 35 33 9 36 35 0 10 32 51 33 10 0 30 49 9 32 30 0 35 36 51 49 35 0 ------------------- I want to do cluster with average method. ---- rown<-c("A",

Hi Everyone, I'm trying to use cutree to get the clusters after hclust. What I used is: mycluster<-cutree(cnclust,h=0.5) Now, my problem is, how can I get the actual clusters? Thanks! Best, Baoqiang Cao

Dear all, I have been trying the following without avail and would be very grateful for any help. From a dendrogram (recursive list of lists with some structure), I would like to obtain some information of the component lists and of the enclosing list at the same time. In dendrogram-speech I basically would like the label of the leaf and the height of the enclosing branch. A dendrogram example

I have tried to use rect.hclust() to draw a rectangle around a set of leaves, but am running into trouble. The rect.hclust() is drawing two rects instead of one, and of the wrong size: -------------------- scoreClusterObj <- hclust(scoreDistanceObj, method=clustMethod) order <- scoreClusterObj$order orderedLabels <- rep(0, length(order)) for (orderIndex in 1:length(order)) { # this

Hi Jenny If you want a general solution I understand. However I just downloaded the file fine (as far as I can tell) so you are welcome to have a copy. I can email it to you if you want. I do not think your test for NA is valid. i.e if(test != "NA"){ } I think you should use if(is.na(test)){ } Or something similar. J --- John Seers Institute of Food Research Norwich

Dear R-Help friends, I am unable to get the latest version of R (2.4.1) to compile on my solaris 10 system - has anybody else experienced this problem and are you able to offer me any advice? I appreciate your time, many thanks, Jenny Barnes Here are my CURRENT specifications: platform sparc-sun-solaris2.10 arch sparc os solaris2.10

Thanks to Andy and Thomas, Reading help(hclust) more carefully would have done it but sometimes you do not see the wood for the trees... So hc$merge does exactly what I want. I have never been aware of the command str to get the structure of an R-object. It seems pretty useful to me. Thanks, Arne > -----Original Message----- > From: Liaw, Andy [mailto:andy_liaw at merck.com] >

Dear R-help, I have performed a hierarchical clustering on some data that I have and would like to know some nice ways of visualizing it. I have 2 related questions: i) How to color the labels AND the terminal branch of a dendogram? This is my inelegant way of just getting the colored labels. data(iris) # Formatting data into required format ir <- iris[ ,-5] ir.class <- c(

Hello, I analyse some free-sorting data so I use hierarchical clustering. I want to compare my proximity matrix with the tree representation to evalute the fitting. (stress, cophenetic correlation (pearson's correlation)...) "The cophenetic similarity of two objects a and b is defined as the similarity level at wich objects a and b become members of the same cluster during the course of

Hi all, I'm new to R and I'm struggling to decipher an error message. Briefly, I am trying to use the pvclust package to do hierarchical clustering of some CGH data. The data is from the Progenetix CGH database. It is arranged as a table where each column is a single case and each row is a single chromosome band. The value in each cell is either 0, 1, 2, or -1. Corresponding to no change,

Hi all, This is the first time I'm writing to R-devel, and this time I'm just asking for the purpose for a certain line of code in stats::as.hclust.dendrogram, which comes up as I'm trying to fix dendextend. The line in question is at line 128 of dendrogram.R in R-3.3.3, at stats::as.hclust.dendrogram: stopifnot(length(s) == 2L, all( vapply(s, is.integer, NA) )) Is there any

Dear R Helpers, I read carefully the documentation and all postings on the hclust and cutree functions, however some aspects of the tree ordering and cluster assignment performed by these functions remain unclear to me, so I would very much appreciate your help in making sure I get them right. Here is an example, with values chosen to illustrate the problems. I have a set of five profiles

Dear all, I'm having some problems getting my recursive function to work. At first I though that maybe my data was too big and I increase option(expressions=50000). Then I thought that I would try it on some smaller data. Still not working. :( I would have thought there should be a function for this already, so any suggestions are welcomed for other methods. I did try igraph but couldn't

kmeans and clara work great. Thank you for the tip. I have another question: Is it possible to weight the observations in a cluster analysis ? I haven't found any mention of this in the kmeans of clara help texts. Moritz Lennert Charg? de recherche IGEAT - ULB t?l: 32-2-650.65.16 fax: 32-2-650.50.92 email: mlennert at ulb.ac.be > On Wed, 25 Apr 2001, Moritz Lennert wrote: >

Hi everybody, I have a problem with a cluster analysis. I am trying to use hclust, method=ward. The Ward method works with SQUARED Euclidean distances. Hclust demands "a dissimilarity structure as produced by dist". Yet, dist does not seem to produce a table of squared euclidean distances, starting from cosines. In fact, computing manually the squared euclidean distances from cosines