similar to: Hclust - Number of branch operations for every element

Hello all, I manually created an hclust object. Now I am looking to reorder the leafs so they won't intersect with each other, and would be happy for advises on how to do that. Here is an example code: #------------------------------------- a <- list() # initialize empty object # define merging pattern: # negative numbers are leaves, # positive are merged clusters (defined by row

Dear group, I am currently struggling with the following problem for a while: I want to create a list whose elements consists of lists themselves. More concise: The list elements are HCLUST objects. However, when I try to append the HCLUST objects to my list via: cluster_list <- append(cluster_list, HCLUSTobject) the HCLUST object is appended - but not as an object but as its components. So

Hallo everybody, I have a question concerning plotting of hclust dendrograms. I created several of those dendrograms and like to plot them in different plots. I'd like to have all plots with the same scaling of the y axis so that they become comparable by eye. That means they should all start at y=0 and end up with a certain given value, e.g. y=8. I tried the following: plot(

Hi, I'm doing hierarchical clustering, and want to export my dendrogram to a tree-viewing/editing software. I can do this by converting the data to Newick format (hc2Newick in ctc package), but I can't get branch lengths to show in the resulting phylogram. I figured it might help to convert my hclust object into a phylo object (as.phylo in ape package), but the following lines give me

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

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

Hi all, it appears that plot.hclust disregards the argument 'cex'. Up until 2.15.1 (and probably all 2.15.x), specifying cex in plot.hclust changed the size of the plotted labels on each leaf. In 3.0.0 the character size remains the same irrespective of the cex setting. Since the help text for plot.hclust does not mention the cex argument, it is possible that an "undocumentde

I want to change leaf color by group in hclust plot. I've seen several answers about A2R package but I cannot install A2R and Rtools in windows. Do you know how to install A2R package in windows or how to change leaf color by group in hclust plot? Thank you in advance, Soyeon

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

Hello dear R-help mailing list members, I wish to create an hclust object which will be based on a customized hierarchical clustering algorithm, programmed in R. After looking into the hclust function, I noticed that the algorithms themselves are implemented in Fortran. In order for me to implement my algorithm in R, it would be very helpful if there was some example of implementing (even one

Hi, I want to know if there is a difference between the two hierarchical methods Agnes and hclust when there are used with the same method and the same metric on the same data! I ask this question because I executed the following program: hc <- hclust(dist(AGRIINSTTableFinaleCR), "ward") agnes<-agnes(dist(AGRIINSTTableFinaleCR),method="ward") And clusters are not the

Good afternoon, After cuting a hierarchical tree using cutree(), how to check correspondances between classes and branches? This is what we do: srndpchc <- hclust(dist(srndpc$x[1:1000,1:3]),method="ward") #creation of hierarchical tree plclust(srndpchc,hmin=20000) #visualisation srndpchc20000 = cutree(srndpchc,h=20000) #returns 4 classes table(srndpchc20000 ) srndclass20000 =

I could not figure out what was the default when I ran hclust() without specifying the method. For example: I just have a code like: hclust(dist(data)) Any input would be appreciated:) [[alternative HTML version deleted]]

The R function hclust is used to do cluster analysis, but based on R help I see no way to print the actual fusion distances (that is, the vertical distances for each connected branch pairs seen in the cluster dendrogram). Any ideas? I'd like to use them test for significant differences from the mean fusion distance (i.e. The Best Cut Test). To perform a cluster analysis I'm using: x

Hi all, The function heatmap uses the functions dist and hclust with default parameters. How to change these parameters? For example, i want to use the ward criterion for hierarchical clustering with binary distance. Best regards, Olivier.

This message is in MIME format. Since your mail reader does not understand this format, some or all of this message may not be legible. ------_=_NextPart_000_01C35A53.75780090 Content-Type: text/plain; charset="iso-8859-1" Anyone have a clue why hclust() and agnes() produce different results in the example below when both use method="average"?? I'm not able to reproduce

Dear List, My dataset is as below: I am using library(cluster) hierarchical clustering on these data. If i try to plot these i couldn't see the partitions clearly, > dd<-hclust(dist(DataSetS01022Full), "ave") > Warning message: >NAs introduced by coercion >(dn<-as.dendrogram(dd)) >plot(dn) please find the link on the plot : http://roughjade.blogspot.com

I've been trying to get plot.hclust to work with a hclust object I created and have not had much success. It seems that there is some "hidden" characteristic of a hclust object that I can't see. This is most easily seen in the following example, where plot.hclust works on one object, but when this object is "dumped" and then re-read, plot.hclust no longer works. Is

I have a data set with 6 variables and 251 cases. The people who supplied me with this data set believe that it falls naturally into three groups, and have given me a rule for determining group number from these 6 variables. If I do scaled.stuff <- scale(stuff, TRUE, c(...the design ranges...)) stuff.dist <- dist(scaled.stuff) stuff.hc <- hclust(stuff.dist)

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