similar to: cauculating dissimilarities in R

Dear All, I get some problems using the 'phylo' and dissimilarity functions in R. I converted an output from 'hclust' into an order of phylo so as to be able to use the 'consensus' function on it. Each time I submit the consensus codes, my computer hangs. When I tried to see what the contents of the object converted into order phylo is, I get the message

Hi I have a large dataset, containing a wide range of binary variables. I would like first of all to compute a jaccard matrix, then do a PCA on this matrix, so that I finally can do a hierarchical clustering on the principal components. My problem is, that I don't know how to compute the jaccard dissimilarity matrix in R? Which package to use, and so on... Can anybody help me? Alternatively

Dear Rhelp,   I did a daisy on 5 lifestyle variables, 3 of which were nominal and 2 were ordinal and assigned types “nominal” and “ordinal” for the variables, respectively.  I got an output indicating their types as “I” for interval(?). Doing it on the Rdata example “flower” gave the same types in the output as the types they were assigned to.  Why is this so? Below are the codes and outputs.  

Dear All , Since dissimilarity is one of quality measures in clustering , I'm trying to access to the sum of dissimilarity as a whole measure. But after running my data using CLARA I obtain : 1128 dissimilarities, summarized : Min. 1st Qu. Median Mean 3rd Qu. Max. 0.033155 0.934630 2.257000 2.941600 4.876600 8.943700 But I can not find the sum of dissimilarity.How can i

I have 4 very large species lists and I would like to compare them. I have the following results from running Sorenson’s dissimilarity tests: Norfolk Fens compared to Suffolk Coastal Fens: QS=0.583961142689298 Norfolk Fens compared to Breckland Edge Fens: QS=0.714896020281379 Norfolk Fens compared to Other Fens:

Hello Martin Maechler and All, A simple question (I hope): How can I compute the "sum of the dissimilarities" that appears in the pam command (from the cluster package) ? Is it the "manhattan" distance (such as the one implemented by "dist") ? I am asking since I am running clustering on a dataset. I found 7 medoids with the pam command, and from it I have the

Hello. I know my dissimilarity matrix but not my original data. Is there any way i could use the clustering function Mclust or EMclust with this dissimilarity matrix? or at least some equivalent of these functions? As this is model based clustering i dont know if it is actually possible to do it without the original data thanks in advance for your help [[alternate HTML version deleted]]

Hello, I'm using dovecot 1.2.11 with virtual folders. I'd like to replace my real INBOX by a virtual one but I have several questions : * will my mail still be delivered to my real INBOX? * will I be able to access my real INBOX, for example using a virtual folder reliyng on INBOX * and, how to do it. Here's my problem, if I look to the wiki page [1], I don't really

Does anyone have a good method for calculating Jaccard coefficients now that the dissimilarity() function is no longer an option? Wen Gu John Jay College of Criminal Justice445 West 59 StreetNew York, NY 10029 wgu@gc.cuny.edu _________________________________________________________________ Express your personality in color! Preview and select themes for Hotmail®.

Hello, I would like to use my own dissimilarity matrix in a PAM clustering with method "pam" (cluster package) instead of a dissimilarity matrix created by daisy. I read data from a file containing the dissimilarity values using "read.csv". This creates a matrix (alternatively: an array or vector) which is not accepted by "pam": A call

Hi, I'm doing a Market Basket Analysis in which I have a list of transaction id's in column 2 and transactions(product names) in column 1. I read this into a transaction file using a txn<-read.transaction(file="data.csv",format='single', rm.duplicates=F, cols=c(1,2)) If I want to use the apriori algorithm everything seems to be running fine. However it is when I want

Hello List, The list sorted my problem thus I shall contribute back ;-) PROBLEM: ======== I am posting this example, where I have a "Reunion" link of 30 channels. If i send all the traffic (proper + mobile) on the link, the less profitable proper traffic fills the link and leaves no channel for more profitable mobile traffic. Some kind of priority is needed to always leave space for

---------- Forwarded message ---------- From: <r-help-owner@r-project.org> Date: 2013/2/8 Subject: vegdist Error en double(N * (N - 1)/2) : tama?o del vector especificado es muy grande To: caro.bello58@gmail.com Message rejected by filter rule match ---------- Mensaje reenviado ---------- From: caro bello <caro.bello58@gmail.com> To: r-help@r-project.org Cc: Date: Fri, 8 Feb 2013

Hi folks, I am new to the R software. I have been going through different materials to know more about R. I have the R software installed on my windows machine.I would like to know the R source code for the following problems on iris flower data set. I need to do the cluster analysis project with the iris data set. The goal is to cluster the flowers according to their Sepal.Length, Sepal.Width,

Hello, I use asterisk to to IAX2 trunking between London POP & Reunion Island pop. I would like to know if it's possible to do a kind of call-limit (i.e. restrict to XX) channels but on a per dialcode and / or destination basis. For example: [trunk] ; reunion proper, i want to send no more than 24 channels exten => _0262XXXXXX,1,Dial(IAX2/mytrunk/${EXTEN}) ; reunion mobile, i want

I have some simple code so that when you click on a thumbnail, it''s supposed to display the image enlarged in the enlargement area. The page looks right, but when you click on a thumb nothing happens, it just moves up the page. Why is the href=# happening ? The generated html comes after the sample rhtml <%= image_tag @enlargement, :width => "279", :height =>

Good morning, I am analyzing a dataset composed by 364 subjects and 13 binary variables (0,1 = absence,presence). I am testing possible association (co-presence) of my variables. To do this, I was trying with cluster analysis. My main interest is to check for the significance of the obtained clusters. First, I tried with the pvclust() function, by using method.hclust="ward" and

Hello Stephen, I am happy that you help me. Thanks a million. It is a good feeling that you confirm my assumption that dsvdis is not able to deal with missing data, because it says me that I am not completely incapable. Okay now I have the problem what to do. I used this function ´cause there is an option to weight columns differently what I haven´t found in other functions. But now I

Hi, According to daisy function from cluster documentation, it can compute dissimilarity when NA (missing) value(s) is present. http://stat.ethz.ch/R-manual/R-devel/library/cluster/html/daisy.html But why when I tried this code library(cluster) x <- c(1.115,NA,NA,0.971,NA) y <- c(NA,1.006,NA,NA,0.645) df <- as.data.frame(rbind(x,y)) daisy(df,metric="gower") It gave this

Hi, I have two questions. First, I'd like to compare a ZINB model to a negativ binomial model with the Vuong test, but I can't find how to performe it from the zicount package. Does a programm exist to do it ? Second, I'd like to know in which cases we have to use a double hurdle model instead of a zero inflated model. Many thanks, St??phanie Payet REES France R??seau