similar to: Clustering with ordinal data

Hi folks, I tried for the first time hclust. Unfortunately, with missing data in my data file, it doesn't seem to work. I found no information about how to consider missing data. Omission of all missings is not really an option as I would loose to many cases. Thanks in advance Holger -- View this message in context:

How should I analysis it in R ???? all the resposes variables are ordinal from 0 to 10. and the explanatory variable is a factor ... -- View this message in context: http://old.nabble.com/Multivariate-problems-.-.-.-with-200-resposes-variables-and-1-explanatory-variable-tp26522912p26522912.html Sent from the R help mailing list archive at Nabble.com.

Hello, In the documentation for agnes in the package 'cluster', it says that NAs are allowed, and sure enough it works for a small example like : > m <- matrix(c( 1, 1, 1, 2, 1, NA, 1, 1, 1, 2, 2, 2), nrow = 3, byrow = TRUE) > agnes(m) Call: agnes(x = m) Agglomerative coefficient: 0.1614168 Order of objects: [1] 1 2 3 Height (summary): Min. 1st Qu. Median Mean 3rd

Hi, I'm trying to apply the function daisy() to a data.frame 10000x10 but I have not enough space (error message: cannot allocate vector of length 1476173280). I didn't imagine I was not able to work with a matrix of just 10000 observations... I have setted in Rgui --max-mem-size=2G (I'm not able to set more space..) How can I solve this issue? Separating observations depending on

I want to compute the distances in a mixed variable matrix using the Gower coefficient. I understand it is possible to calculate distances in a matrix with mixed variables using the dudi.pco command. How would this work? Jorine

Hi there fellow R users, R has many different clustering packages (e.g. mclust,cluster,e1071). However, can anyone recommend a method to deal with data sets that contain categorial and continuous variables? Regards Wayne KSS Ltd Seventh Floor St James's Buildings 79 Oxford Street Manchester M1 6SS England Company Registration Number 2800886 Tel: +44 (0) 161 228 0040 Fax: +44 (0)

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, First I should note I am relatively new to R so I would appreciate answers that take this into account. I am trying to perform an MDS ordination using the function ?metaMDS? of the ?vegan? package. I want to ordinate species according to a set of functional traits. ?Species? here refers to ?sites? in traditional vegetation analyses while ?traits? here correspond to ?species? in such

Hello I've been asked to help evaluate a vegetation data set, specifically to examine it for community similarity. The initial problem I see is that the data is ordinal. At best this only captures a relative ranking of abundance and ordinal ranks are assigned after data collection. I've been trying to find a procedure in R that can handle ordinal based classification and so far have

Hello I have 2 rows in a matrix and I want to calculate the Gower Distance between the 2 , how can I do it? I searched and found nothing that can help me, and my program doesn't know the gdist function and I couldn't find it on the R help site. Can anyone help me plz Thank u all [[alternative HTML version deleted]]

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

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

Dear r-Community, Step1: I would like to calculate a NMDS (package vegan, function metaMDS) with species data. Step2: Then I want to plot environmental variables over it, using function envfit. The Problem: One of these environmental variables is cos(EXPOSURE). But for flat releves there is no exposure. The value is missing and I can't call it 0 as 0 stands for east and west. Therefore I

What function and package I use to conduct ordinal regression?? My data is composed 2colums and 180rows. The first colum indicate level of mass and second colum is intensity. So, I want to calculate how much intensity are related mass. [[alternative HTML version deleted]]

Hi, I just wanted to check whether there is a clustering package available for ordinal data. My data looks something like: #1 #2 #3 #4..... A B C D... D B C A... D C A A... where each column represents a sample, and each row some ordinal values. I would like to cluster such that similar samples appear together. thanks! [[alternative HTML version deleted]]

I have a data which contain some NA value in their elements. What I want to do is to **perform clustering without removing rows** where the NA is present. I understand that `gower` distance measure in `daisy` allow such situation. But why my code below doesn't work? __BEGIN__ # plot heat map with dendogram together. library("gplots") library("cluster")

I'm working on a project related to document clustering. I know that R has clustering algorithms such as clara, but only supports two distance metrics: euclidian and manhattan, which are not very useful for clustering documents. I was wondering how easy it would be to extend the clustering package in R to support other distance metrics, such as cosine distance, or if there was an API for

Hi, I am working with a species-by-trait .csv file (columns=traits, rows=species) and get the following warning message when trying to plot results of both metaMDS and pcoa:  "Warning message: In ordiplot(x, choices = choices, type = type, display = display,  :   Species scores not available" I am using a Gower's transformation in both procedures within the metaMDS or pcoa

Hello to all, I'm new to R so I have a lot of problems with it, but I'll only ask the main one. I have clustered an environmental matrix with 2 different methods, and I'd like to plot them in a PCA and a db-RDA. I mean, I want see these clusters in the plots like points of differents colours, together with the rest information of the plot, but I don't know how to do this.

Hello there, I'm trying to plot vectors with p<0.1 in a NMDS ordination plot using p.max. Below the scripts I'm using. I guess I'm missing something! could you please give me a hand? species<-metaMDS(species_matrix)ef<-envfit(species,environmentaldata_file,permu=999,na.rm=TRUE)efplot(species, dis="sites")plot(ef,p.max=0.1) Error in plot.envfit(ef, p.max = 0.1) :