similar to: AW: estimating number of clusters ("Null or more")

Hi all, once more about the old subj :-) My data has too much various distribution families and for every particular experiment I need just to decide whether the data is "quite homogeneous" or it has two or more clusters. I've revisited the following libraries: amap, clust, cclust, mclust, multiv, normix, survey. And I didn't find any ready-to-use general

Hi I have two questions, the first perhaps dumber than the second. Firstly, I have a data set, and when I plot a histogram it looks like a normal distribution. So I want to overlay a bell-shaped normal distribution on top of it, to demonstrate how similar it is to the normal distribution. I have read the help on dnorm(), rnorm(), pnorm() etc but still can't figure out how to plot a normal

Hi, After problem described in http://oss.oracle.com/pipermail/ocfs2-users/2010- December/004854.html we've upgraded kernels and ocfs2-tools on every node. The present versions are: kernel 2.6.32-bpo.5-amd64 (from debian lenny-backports) ocfs2-tolls 1.4.4-3 (from debian squeeze) We didn't noticed any problems in logs untill last friday, when the whole ocfs2 cluster crashed. We know

Hi All, I am trying to cluster a one-dimensional data (see the file attached) using Mclust() but got an error message like: >Mclust(x) Error in rep(1, n) : Object "n" not found When I do a simulation sometimes it works sometimes doesn't. >Mclust(c(rnorm(50),rnorm(56,-0.5))) Error in rep(1, n) : Object "n" not found >Mclust(c(rnorm(56),rnorm(56,-0.5))) best

> > It would be nice not only for me. > > I agree totally. If you belong to R-contributors group then thanks a lot in advance! > The problem is that you have to formalize what a cluster is, > and this is not a well defined notion. > It has different meanings in different applications. you are right if one follows the idea of full formalization of the notion it

Dear group, I want to use the mclust package on large data, and therefore I want to use a subset in the initial clustering phase. From help(mclust): k: If `k' is specified, the hierarchical clustering phase will use a sample of size `k' of the data in the initial hierarchical clustering phase. The default is to use the entire data set. m2 is a

Dear R-users, I have a two - dimensional data set which needs to be clustered into groups: I'm searching for groups of points which show a positive correlation (in a twodimensional plot of the data set), but I do not have any knowledge about how many groups there might be. Do you know of a clustering algorithm in R (or in general) which can use a-priori information about the cluster's

Hi, I would like to know if someone knows an extended implementation of k-means in R to find appropriate number of clusters for a given k-dimensional data. Also, I am working on clustering for forecasting, if someone is interested or has knowledge on implementational details please mail me, I would appreciate it. Regards Skanda Kallur "Cogito, ergo sum" (I think, therefore I

Hi A few days ago I upgraded debian8 to debian9 dovecot is from source # 2.2.36.4 (baf9232c1): /etc/dovecot/dovecot.conf # Pigeonhole version 0.4.24.2 (aaba65b7) # OS: Linux 4.9.0-13-amd64 x86_64 Debian 9.13 Today I get some times in logs: "dovecot-uidlist line 112: Invalid data" and I dont know why This is claster dovecot: dovecot1 - debian8 dovecot2 - debian8 dovecot3 - debian8

I'like to do cluster analysis by using mahalanobis distance. Could you tell me how to do?

Hi everybody, I'd like to know if there's an easy way for extracting outliers record from a dataset, in order to perform further analysis on them. Thanks Alessandro

Hi, I have ~40,000 rows in a database, each of which contains an id column and 20 additional columns of count data. I want to cluster the rows based on these count vectors. Their are ~1.6 billion possible 'distances' between pairs of vectors (cells in my distance matrix), so I need to do something smart. Can R somehow handle this? My first thought was to index the database with

Dear all, I'm fitting a set of length-of-stay data by a model of mixture of exponentials. I've been following the example on page 436 in MASS (5th Ed.). However, I have a couple of questions while following this example. What if we don't know how many components there are in the model in advance. Is there any established method to determine the number of components from a set of

Hello all (especially MCLUS users). I'm trying to make use of the MCLUST package by C. Fraley and A. Raftery. My problem is trying to figure out how the (model) identifier (e.g, EII, VII, VVI, etc.) relates to the covariance matrix. The parameterization of the covariance matrix makes use of the method of decomposition in Banfield and Rraftery (1993) and Fraley and Raftery (2002) where

Hi all, I am running a series of experiments where after manipulating my data I run several clustering algorithms (agnes, diana and a clustering method of my own) on the data. I wanted to determine which clustering method did the best job, so therefore I had defined my own quality measure using two criteria: compactness of the data within the clusters themselves and the amount of seperation

Dear R users, I am interested in clustering in R. In SAS we have some criteria for determining the number of clusters using the PROC CLUSTER procedure, which are "CCC" cubic clustering criterion (Sarl 1981), Psuedo F (PSF), and Psuedo T square (PST). My question is do thsese criterion exists in R, I tried to search and got one hit (BIC) in Mclust, which I am aware of, any input is

Hi list, not really a problem to solve but a strange unwanted behavior (at least I do not like it): I'm loading library(multiv) to use sammon. Later I load library(MASS) which tells me that sammon is masked now, because there is also a MASS version of sammon. Since I believe that the MASS version is at least as good as the multiv version, I would also use the MASS version, but help(sammon)

Hi, I have run rpart to construct a regression tree. Is there any simple method to draw a nice picture of it, as it is usually done in books and paper to visualize the tree? Thank you, Christian *********************************************************************** Christian Hennig Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg hennig at math.uni-hamburg.de,

Hi, exist a special cluster-analysis algorithms which can work with NA's. a further "problem" is that i want cluster variables not cases to identify special variable-set's. Is it a common way turn the data.frame and use kmeans,because this works with NA's, or have anybody another method for finding "variable-sets" , with exception of factor analysis. thanks for

Hello list, I try to optimize some R code and it turns out that the function as.matrix takes a lot of time in my code. There is only one reason why I need as.matrix: My code should work for matrices with ncol=p and p should be allowed to be 1 or larger. Now I have a matrix x with dim(x)=(n,p), and I need to work with the submatrix y <-x[gv,], (gv a vector of n logicals) and to calculate