search for: dissimilarity

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 b...

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...

Dear List, This is Elaine, a postgraduate studying in bird distributions in East Asia. I want to calculate Simpson dissimilarity index, based on a presence/absence matrix of bird species in islands in East Asia. (matrix row: 36 islands/matrix column: species ID) (R package vegan to make NMDS and R package betapart) In most papers using vegan for NMDS and betapart for dissimilarity index, the dissimilarity index is gen...

Hi all, I'm trying to perform a hierarchical clustering on some dissimilarity data that I have but the data matrix I have already contains the dissimilarity values. These values are calculated using a separate program. The dissimilarity matrix in complete with no missing values but the hclust, and agnes routines require it in the form produced by daisy or dist. Is there...

Hi, I'm trying to use a similarity matrix (triangular) as input for pam() or fanny() clustering algorithms. The problem is that this algorithms can only accept a dissimilarity matrix, normally generated by daisy(). However, daisy only accept 'data matrix or dataframe. Dissimilarities will be computed between the rows of x'. Is there any way to say to that your data are already a similarity matrix (triangular)? In Kaufman and Rousseeuw's FORTRAN implementatio...

...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 I'm search for another way to explore the clusters present in my data. Another problem is, that I have cases with missing values on different variables. Jacob -- View this message in context: http://r.789695.n...

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 ga...

Is there a way of extracting mean distance or dissimilarity for a given strata from a 'dist' or 'dissimilarity' object, e.g. extract mean distances for each species in Anderson's iris data? data(iris) iris.dist<-dist(iris[,1:4]) then what? Mikkel Grum, PhD Genetic Diversity Scientist International Plant Genetic Resources Instit...

...0 0 0 0 2 0 1 0 0 1 1 0 0 0 3 1 0 0 1 0 0 0 0 0 4 0 1 0 0 1 0 0 0 0 5 0 1 0 0 0 0 0 0 0 each with 348 rows. I would like to perform a simple matching but only row 1 compared to row1, row 2 compared to row 2 (paired).......giving back a number as dissimilarity for each comparison. How can i do that? Thanks in advance Birgit Birgit Lemcke Institut für Systematische Botanik Zollikerstrasse 107 CH-8008 Zürich Switzerland Ph: +41 (0)44 634 8351 birgit.lemcke@systbot.uzh.ch [[alternative HTML version deleted]]

I have a matrix of similarity scores that I want to convert into a matrix of dissimilarity scores so that I can apply some clustering methods to the data. That is, high values in my matrix signify similarity and low values (zero being the lowest) signify no similarity. What functions/options in R or its packages are available for making this kind of transformation of a matrix? Spe...

Dear List, is there an elegant (or even not elegant) way how to transform dissimilarity or distance matrix A (or, in general, arbitrary symmetrical matrix) by transposition of rows and columns into a form closest to "block diagonal" matrix B? The matrix A is adjusted the following way A[A<epsilon] <-0 #(epsilon is given "small" number) B: (in its ideal form...

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 t...

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...

Hi, I have a set of nodes and a dissimilarity matrix for them, as well as a csv file in which the diss matrix has been converted to [node_1, node_2, dissimilarity] format. I would like to visualize this as a graph in Euclidean space (that is, similar nodes clumped together in clusters), rather than the seriation visualization given by dissplo...

...r cluster, centroids, etc. So, here are my questions. 1) Can isoMDS work only with dissimilarities? Or, is there a way that it can perform the analysis on the similarity matrix as I have described it? 2) If I cannot perform the analysis on the similarity matrix, how can I turn this matrix into a dissimilarity matrix necessary? I am less familiar with this matrix and how it would be constructed? Thanks for any help offered, Harold a b c d e f g h i j a 4 2 4 3 3 2 0 0 0 0 b 2 4 2 3 1 0 2 2 2 2 c 4 2 4 3 3 2 0 0 0 0 d 3 3 3 4 2 1 1 1 1 1 e 3 1 3 2 4 3 1 1 1 1 f 2 0 2 1 3 4 2 2 2 2 g 0 2 0 1 1 2 4 4...

Hello, I want to make a fuzzy classification from a dissimilarity matrix (calculated with daisy from package 'cluster'). I have tried to use fanny (package cluster) but I have the same problems than described in a previous message (http://tolstoy.newcastle.edu.au/R/help/05/05/4546.html) i.e. it always gives me two clusters in the results (even if k is dif...

...8 are interval scaled. Commands to load the dataset in R. library(cluster) data(flower) flower What are the different types of dissimilarities that can be calculated on such a dataset? Do I need to group the types of variables first i.e. all binary together then run the calculation? Do I use dissimilarity indices such as Jaccard or should it be classification function such as ?daisy? which should be used? Many thanks, Elvina Payet (MSc) University of La Reunion

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: QS=0.78572348898302 Suffolk Coastal Fens compa...

Dear David, you asked this question a while ago on the R mailing list and got no answer. I have the same problem and was wondering if you had found a solution Cheers Loic Loic Thibaut, PhD candidate, ARC Centre of Excellence for Coral Reef Studies, School of Marine Biology, James Cook University, Townsville, Qld, 4811, Australia. Tel + 61 747 815 735, Fax: + 61 747 251 570, email:

Hello R-user community! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) Presently I try to run the function metaMDS (vegan) using an existing dissimilarity-matrix. As I would like to start with this matrix I thought I could just give the matrix using the x= -argument Test<-metaMDS(x=Dist.Gower) Fehler in inherits(comm, "dist") : Argument "comm" fehlt (ohne Standardwert) But obviously that is not the way it works. The...