similar to: Changing distance scale in plclust()

Hello everyone, Does anyone know how to implement the argument "unit" in R's plclust function ? I used to use Splus where this argument exists but it has not been implemented in R's plclust. The reason why I switched from Splus to R is that Ward's method is not implemented for S's hclust whereas it is implemented for R's hclust. What I would need is S's plclust

Hi all, I need to plot a dendrogram, but I built a hclust object. Follow the code lines: >dendObject<-list(merge=merge,height=height,order=order,labels=labels,call="hclust(d=d)",method="complete", dist.method="euclidean") >class(dendObject)<-"hclust" >plclust(dendObject,axes=FALSE) Error in cl[[2]] : subscript out of bounds Anybody can help

I use hierclust (hierarchical clustering) in multiv package. In the documentation it is said that plclust (plotting a dendrogram) is available in S-plus. Can I find it anywhere (I have searched through http://lib.stat.cmu.edu/S and found only quotations of plclust in multiv) or is it only part of the S package (which I don't have)? Thanks --------------- Charles RAUX, Laboratoire

>>>>> Ross Ihaka writes: > I have got a little side-tracked (from graphics) and am putting > together a little multivariate analysis library. This is just > intended to be a "core" library rather than anything exhaustive. > Mainly it is a matter of putting togther code which already exists at > StatLib. Here is my present list (only some of which is

Hey Everyone! I wanted to carry out Hierarchical clustering using distance matrices i have calculated ( instead of euclidean distance etc.) I understand as.dist is the function for this, but the distances in the dendrogram i got by using the following script(1) were not the distances defined in my distance matrices. script: var<-read.table("the distance matrix i calculated",

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(

Dear All, I would like to use the simprof function (clustsig package) but the available distances do not include Jaccard distance, which is the most appropriate for pres/abs community data. Here is the core of the function: > simprof function (data, num.expected = 1000, num.simulated = 999, method.cluster = "average", method.distance = "euclidean", method.transform =

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 =

Hi, I am new to clustering and was wondering why pvclust using "maximum" as distance measure nearly always results in p-values above 95%. I wrote an example programme which demonstrates this effect. I uploaded a PDF showing the results Here is the code which produces the PDF file: ------------------------------------------------------------------------------------- s <-

Hi all, I'm new to R, so needless to say I have a couple questions (which I hope I haven't missed through the documentation). I have several files in lower triangular matrix form. For each of these matrices, I want to perform some form of hierarchical clustering on each matrix and capture the output of the clustering. The first problem I run into is actually loading the matrix file

Thanks a lot, Michael! I cc to R-help, where this question really belongs {as the 'Subject' suggests itself...} -- please drop 'bioconductor' from CC'ing further replies. >>>>> "michael" == michael watson (IAH-C) <michael.watson at bbsrc.ac.uk> >>>>> on Thu, 17 Jun 2004 09:16:59 +0100 writes: michael> OK, admittedly it

im using plclust and want the labels to be different colors. i took a look at getS3method("plot","hclust") and saw a call to .Internal. i looked at the help on .Internal and dont know where to go next. any help appreciated! thanks, rafael

heatmap.2 defaults to dist for calculating the distance matrix and hclust for clustering. Does anyone now how I can set dist to use the euclidean method and hclust to use the centroid method? I provided a compilable sample code bellow. I tried: distfun = dist(method = "euclidean"), but that doesn't work. Any ideas? library("gplots") library("RColorBrewer") test

Hi, I have similarity value between string pairs in a mysql database. I need to construct the distance matrix which hclust can take and cluster the strings. Most of the examples I came across show how to construct the distance matrix using dist function. How can I code to construct distance matrix using the data in mysql db. Thanks a lot for any help. [[alternative HTML version deleted]]

Use something like hclust(as.dist(mydist), ...) ought to work. Andy -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of ucecgxu at ucl.ac.uk Sent: Wednesday, January 18, 2006 4:47 PM To: r-help at stat.math.ethz.ch Subject: [R] r-help, how can i use my own distance matrix without using dist() Dear R-helpers, i am a

i have a dataset with x and y values. i want to randomly select a point on the x-axis between the smallest and largest x-value and use a y value of zero for them. Next, for each randomly selected point {x[i],0}i want to find the point in the {x,y} space which is closest to them. However, as seen below, the scale of y-values is not the same as the x-values, using normal distance would always end

I frequently use hclust on a similarity matrix. In R only a distance matrix is allowed. Is there a simple reliable transformation of a similarity matrix that will result in a distance matrix making hclust work the same as S-Plus with a similarity matrix? Venables & Ripley 3rd edition implies that a simple reversal of values will suffice. Thanks -Frank -- Frank E Harrell Jr

Hello, Im working on a 50933 point count bird abundance dataset. I've succeeded in calculating a distance matrix for this entire set, but I don't have sufficient memory to convert this to a matrix, as below... abun.dist <- dist(abun.mat[1:50993,1:235) test <- rowMeans(as.matrix(abun.dist)) Error in matrix(0, size, size) : too many elements specified ive been able to run a hclust()

Dear R I recently performed a cluster analysis. It produced the dendogram no problem but unfortunately the font size of the row.names were all cluttered due to their large size So I tried to change the font size using plclust(cluster.results, labels=iris$specie, cex=0.8) and R came back to me saying Error in plclust(cluster.results, labels = iris$specie, cex = 0.8) : unused argument(s)

Dear friends I reformulate the question. I think I did not formulate it properly. I have some data on some sites. I can define a dissimilarity between each pair of sites. Using this dissimilarity, I have clustered the sites using the hclust algorithm, with method ward. I then obtain 48 clusters, by cutting the tree using cutree with k=48. I would now like to estimate the distance between