similar to: cluster - clusplot.default (PR#1249)

(I tried to send this earlier, but it doesnt seem to have come through, due to problems on my system) Hola: Both cannot be correct: > m <- matrix(1:4, 2) > svd(m) $d [1] 5.4649857 0.3659662 $u [,1] [,2] [1,] -0.5760484 -0.8174156 [2,] -0.8174156 0.5760484 $v [,1] [,2] [1,] -0.4045536 0.9145143 [2,] -0.9145143 -0.4045536 > La.svd(m) $d [1]

When R prints warnings, they often go "out of the line", it would be better if they where wrapped with writeLines(strwrap ... I tried to do that , changing the function warnings, but it has only effect when called explicitely, not when R prints the warnings unasked. Anyhow, here is the changed warnings: warnings <- function (...) { if (!(n <- length(last.warning)))

Hello I am using the following command but not able to text the values on the graph can someone please make suggestions for improvement #here is the command loc_mds <- cmdscale(dist.r, k = 7, eig = TRUE) loc_mds$eig sum(abs(loc_mds$eig[1:2]))/sum(abs(loc_mds$eig)) sum((loc_mds$eig[1:2])^2)/sum((loc_mds$eig)^2) x <-loc_mds$points[,1] y <-loc_mds$points[,2] plot(x, y,

....in example data <- read.spss("c:/data.sav",use.value.label=F,to.data.frame=T) try help(read.spss) ! regards,christian kjetilh at umsanet.edu.bo schrieb am 28.08.02 02:08:39: > Hola! > > Can the foreign package now read data from spss 10? > > Kjetil Halvorsen > -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- > r-help

Hola! look at the following: > test <- function() { + options(warn=-1) + on.exit( options(warn=0)) + log(-1) + } > test() [1] NaN but what should be better, doesnt work: > test1 <- function() { + oldwarn <- options("warn") + options(warn=-1) + on.exit( options(warn=oldwarn)) + log(-1) + } > test1() Error in options(...) : warn parameter

Hello, We are trying to find a function to compute "stress" in our multidimensional scaling analysis of a dissimilarity matrix. We've used "dist()" to create the matrix and "cmdscale()" for the scaling. In order to determine the number of dimensions we would like to plot stress vs. dimensions. However, we cannot find a pre-made command. It seems that other

Dear all, I have a question about the chisq.test command. As an option one can chose the computation of p-values by Monte-Carlo simulation (simulate.p.value=T). Is there any documentation available how this calculations are done and how this simulation based test behaves in small samples? Thanks Klaus Abberger University of Konstanz, Germany [[alternate HTML version deleted]]

Hello, I have a dilemma that I'm hoping the R gurus will be able to help resolve. For background: My data is in the form of a (dis)similarity matrix created from taking the inverse of normalized reaction times. That is, each cell of the matrix represents how long it took to distinguish two stimuli from one another-- a square matrix of 45X45 where the diagonal values are all zero (since this

(I sent this earlier, but it seems not to have come through, due to problems witkh my system) The following command from appendix A, "a sample session", isnt correct: contour(x, y, fa, nint=15) when used R protests: Warning message: parameter "nint" couldn't be set in high-level plot() function it should probably be nlevels, as used a few lines before. This is

The following problem occurs in R 1.4.0 and 1.3.1 for Windows95, but not in R 1.2.0 for Windows95. The problem does not occur in R 1.4.0 for Linux PC, Linux Alpha and HP-UX. Sometimes, the type of 'Size' of an object of type 'dist' changes from integer into double. Running cmdscale on such a 'dist' object gives invalid results. I don't know what should be considered

I am in the process of setting up R1.3.1 on a new computer running windows 2000. I am having problems running the PFE text editor simultaneously within R for editing functions and outside R for editing ordinary text files. The PFE editor behaves as I expected, if it is opened in R AND but no other PFE window is open outside R. Similarly, it also works fine if I am editing a text file outside

Hi, I want to know which distance is using in the function kmeans and if we can change this distance. Indeed, in the function pam, we can put a distance matrix in parameter (by the line "pam<-pam(dist(matrixdata),k=7)" ) but we can't do it in the function kmeans, we have to put the matrix of data directly ... Thanks in advance, Nicolas BOUGET

I am resubmitting this to r-bugs, since Thomas Lumley indicates that it might be an error: On Wed, 5 Jul 2000, Thomas Lumley wrote: > On Wed, 5 Jul 2000, halvorsen wrote: > > > Hola! > > > > I have the following simple function: > > > > > testcar > > function(pow){ > > ob <- glm(Pound~CG+Age+Vage,data=car,weights=No, > >

Hello, I'm using bwplot to make a few plots. The plots are exactly what I need, but are coming out with a grey background and turquoise boxes and whiskers. I cannot figure out how to just get black and white to be the default. Can anyone help me with this? Thanks Kenneth E. Nussear Phone 775 784-1703 Ecology, Evolution and FAX 775 784-1369

Dear R folk: Perhaps I'm just dense today, but I am having trouble reproducing the principal components plotted and summarized by clusplot. Here is a brief example using the pluton dataset. clusplot reports that the first two principal components explain 99.7% of the variability. But this is not what princomp is reporting. I would greatly appreciate any advice. With best regards, -- Tom

Hello, I have a large data set that has more columns than rows (sample data below). I am trying to perform a partitioning cluster analysis and then plot that using pca. I have tried using CLUSPLOT(), but that only allows for 'princomp' where I need 'prcomp' as I do not want to reduce my columns. Is there a way to edit the CLUSPLOT() code to use 'prcomp', please? #

chisq.test with simulate.p.value=TRUE uses the Patefield algorithm, this is not documented, and the original reference is not given, as it ought to be. The reference is: Patefield,W. M. (1981) An efficient method of generating r * c tables with given row and column totals (algorithm AS 159). Applied Statistics 30, 91-97. Kjetil Halvorsen

Dear people, I used clusplot to plot a partition result. The partition result was from pamk with a distance object as input. Then I applied cmdscale on the same distance object for coordinates to make another scatterplot. My problem is this: the coordinates from the cmdscale calculation, though with the same shape, were different in scale and rotation from the scatter plot yielded by clusplot.

This morning I had 37 messages from the r-help list in my mailbox. I think its becoming excessive for an e-mail list. I wonder if whoever looks after this list could either move or gateway it to a usenet group? That would also eliminate the need for special purpose archiving and searching facilities since the site: http://groups.google.com would automatically provide that. That site also

Dear all I'm trying to run a cluster analysis with R Here are the commands: mydata <- na.omit(matrix) # listwise deletion of missing mydata <- scale(matrix) # standardize variables fit <- kmeans(mydata, 8) # 8 cluster solution # get cluster means aggregate(mydata,by=list(fit$cluster),FUN=mean) # append cluster assignment mydata <- data.frame(mydata, fit$cluster)