similar to: imput data in cclust

Dear R users, When I run the following code, R crashes: require(cclust) x <- matrix(c(0,0,0,1.5,1,-1), ncol=2, byrow=TRUE) cclust(x, centers=x[2:3,], dist="manhattan", method="kmeans") While this works: cclust(x, centers=x[2:3,], dist="euclidean", method="kmeans") I'm posting this here because I am not sure if it is a bug. I've been searching

I have checked that section already. Sorry, I should have mentioned that. Memory limit increase does not work. Installtion of msvcrt.dll does not work either. Thank you. -----Original Message----- From: ripley at stats.ox.ac.uk [mailto:ripley at stats.ox.ac.uk] Sent: Wednesday, March 05, 2003 2:44 PM To: Igor Oleinik Cc: r-help at stat.math.ethz.ch Subject: Re: [R] problem with cclust[er]

Hi, I'm trying to debug a function I wrote to calculate the cindex for a hierarchical tree. For this it is useful to compare my calculations with those in output from the clustindex function, in the cclust library. There's no way, however, to have the cindex value for a given output of the cclust function, as a NA value is always returned. This happens almost surely because the cindex in

To Whom It May Concern, I am currently trying to use R to perform a "kmeans" clustering of a three dimensional data set. In the directory R-1.5.1/library/cclust/data/ I have created a file that has the following format (only the first few lines are shown for brevity): B X.Vtl X.Vtu 1 -0.529043 1.307031 1.625169 2 -0.752502 1.132813 1.480548 3

Hello, here is my problem, After looking at the mail archives, I found a description of the error I get when I use this package. At first I even tought that they were showing how to solve it. But the thing is that by saying "the programmer forgot drop=FALSE" doesn't show me how I should get rid of the problem I have looked inside the package very quickly and I found three

There is a new version of the 'CCLUST' package ,where i removed the extra command for the kmeans algorithm in the .R programm and also the comments about it in the .Rd help page. Now in the cclust library the kmeans algorithm can be applied only by using the cclust function. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

There is a new version of the 'CCLUST' package ,where i removed the extra command for the kmeans algorithm in the .R programm and also the comments about it in the .Rd help page. Now in the cclust library the kmeans algorithm can be applied only by using the cclust function. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

hi, What is the significance of the 2nd arg in cclust, the 'number of clusters'. I have one matrix with two columns representing x,y coards. I'd like to see how random the distributions is. If I try cclust with 'number of clusters' 1 I get an error, > 1 works though. j. -- ...................... ..... Jason C. Leach .. Current PGP/GPG Key ID: 43AD2024

I'm not sure if this is the correct place to email for this kind of thing, but I couldn't find any other contact info. Also, I am new to llvm, so please try to be understanding. I keep getting an error when I try to compile a simple Hello World program (as a test)(error included below). The error is: Clang: warning: unable to find a Visual Studio installation; try running Clang from a

Hello, I am calling cclust function in cclust package repeatedly until some ceratain conditions for a cluster are met. Unfortunately, the system crashes on the second call (after debugging). # kmeans res1 is a well defined matrix cl <- cclust(res1, as.numeric(ncntrs), iter.max = 20, verbose = FALSE, dist="manhattan", method="kmeans") RGui has generated errors and will

Hi, I am using the following syntax to enter data and perform a cluster analysis: x <- read.table ("clstrdbt.csv", header=TRUE, sep = ",",fill = TRUE) cl<-cclust(x,4,20,verbose=TRUE,method="kmeans") This is the result I receive: Error in cclust(x, 4, 20, verbose = TRUE, method = "kmeans") : (list) object cannot be coerced to type 'double'

Hi all, Why subscripting a one column matrix drops one dimension? > x<- matrix(rnorm(100), ncol=1) > str(x) num [1:100, 1] -0.413 -0.845 -1.625 -1.393 0.507 ... > str(x[20:30,]) num [1:11] -0.315 -0.693 -0.771 0.448 0.204 ... > str(x[20:30]) num [1:11] -0.315 -0.693 -0.771 0.448 0.204 ... This breaks: > cov(x) [,1] [1,] 0.9600812 >

Hi All, while looking why the cclust(cclust) doesn't work for 1-dimensional data, I've found unpleasant behavior in semantics of R. Indeed: is.matrix(matrix(cbind(c(1,2,3,4)),ncol=2)[1:2,]) == TRUE but: is.matrix(matrix(c(1,2))[1:2,]) == FALSE kind regards, Valery A.Khamenya --------------------------------------------------------------------------- Bioinformatics

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'd like to apply some of the cluter indices, using 'clustindex' in the cclust package, but using output from hierarchical clustering using 'hclust' in the mva package. The two packages use a different format for storing the results of clustering; has anyone coerced one into the other? Thanks! -John Barnett

Hi all, I am wandering.. is it possible to cluster data which is in a single column ? for example.. I have some data as follows: 4013 7362 7585 9304 11879 14785 21795 30500 30669 30924 33988 36975 40422 42911 50501 51593 53729 54338 55497 57337 61993 62601 66229 69815 69933 70760 71340 75921 83972 90134 91061 . . . is it possible to cluster this data since it is in a single column ? I have

Full_Name: Chris Hane Version: 2.10.1 OS: Windows Submission from: (NULL) (198.203.181.181) When using barchart in the flexcust package, setting mcol=NULL to avoid the lollipops causes an error. Each panel shows the text message "Error using packet n replacement has length zero." where n is the panel number. > data(iris) > cl <- cclust(iris[,-5], k=3) > barplot(cl,

I have to solve a clustering problem. My first step is to determinate the number of clusters, that's why I 'm using the Calinski index ( [tr(b)/(k-1)]/[tr(w)/(k-1)] ) which i try to maximize to have the best number of clusters. A function is already implemented in R to calculate this index : clustIndex(cl,x, index="calinski") where cl is the result of a clustering method ,

hi, I'm a bit new to R and need a hand importing data. I have a text file of (x,y) pairs like: x,y x,y x,y I can read them in fine with read.table(), but I need to do some cluster analysis on them, so I need it in a format cclust will understand, namely a Matrix. Can anyone help with the code to to convert the data type? Thanks, j. -- ...................... ..... Jason C. Leach ..

> Well, that is in all good texts on R, together with the > solution: drop=FALSE. See ?"[" for the on-line details. OK. Thank you a lot. Now patched cclust and clustIndex work fine for 1D case. BTW, why not to apply the "drop=F" to these functions? I guess other users need 1D case as well. kind regards, Valery A.Khamenya