similar to: MASS: isoMDS and sammon

I'm not sure this list is the right place for this thing. I noticed some erratic behaviour in sammon(). Running sammon on two nearly identical sets of data results in very different results. Below is an example. I create an initial configuration with cmdscale() and store it into 'vec1'. I write this to file, and read it back in again to 'vec2'. According to cor() on the three

Dear all, I'm trying to get a two dimensional embedding of some data using different meythods, among which princomp(), cmds(), sammon() and isoMDS(). I have a problem with sammon() because the coordinates I get are all equal to NA. What does it mean? Why the method fails in finding the coordinates? Can I do anything to get some meaningful results? Thank you very much Domenico

Dear All, I am in the somewhat unfortunate position of having to reproduce the results previously obtained from (non-metric?) MDS on a "kinship" matrix using Statistica. A kinship matrix measures affinity between groups, and has its maximum values on the diagonal. Apparently, starting with a nxn kinship matrix, all it was needed to do was to feed it to Statistica flagging that the

Dear useRs, last week I asked you about a problem related to isoMDS. It turned out that in my case isoMDS was trapped. Nonetheless, I still have some problems with other data sets. Therefore I would like to know if anyone here has experience with how well isoMDS performs in comparison to other non-metric MDS routines, like Minissa. I have the feeling that for large data sets with a high

Hi all, I'm trying to perform an MDS of some data that I have. When I use cmdscale everything is fine and I get some interesting results however, the tends to be low. What I wnat to do is compare this with the Non-Metric MDS using isoMDS or sammon. However, when I try using these I get the following message. Error in isoMDS(x.dist) : zero or negative distance between objects 2 and 4

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

Hi, I'm trying to use isoMDS to project a directed graph to 2-dim vectors, but I got an error. #here is the code to create the graph using igraph package and run isoMDS on it. library(igraph) library(MASS) g<-make_graph(c(1,2, 2,3, 2,4, 3,4, 4,5, 5,6, 3,6, 1,6, 2,5),directed=TRUE) dist<-distances(g, mode="out") loc<-isoMDS(dist) # below is content of the dist matrix

Hello, I am inputing a 17 x 17 symetric matrix to sammon. The matrix is a co-occurance matrix with no missing data. If this is at all relevant, running hclust on this matrix works. > samx <- sammon(q23axproduct) I receive the following error: Error in sammon(q23axproduct) : initial configuration must be complete In addition: Warning messages: 1: some of the first 2 eigenvalues are

Hi, I'm trying to do a non-metric multidimensional scaling using isoMDS. However, I have some '0' distances in my data, and I'm not sure how to deal with them. I'd rather not drop rows from the original data, as I am comparing several datasets (morphology and molecular data) for the same individuals, and it's interesting to see how much morphological variation can be

Hello, I have a data set on which I run the sammon algorithm as follows: library(MASS) data = read.table('problemforr.dat') y = cmdscale(data, add=TRUE) s = sammon(data, y$points) (In case it should be relevant, I make the data available at http://idi.ntnu.no/~edsberg/problemforr.dat) With R 2.2.1 on Debian Sid I always get one of two solutions (stress 1.74288 after 10 iterations or

Hi, I am looking for the best multidimensional configuration for my data (47*47 distance matrix). I ve tried classical metric (cmdscale) and non metric MDS (isoMDS, nmds) but it is now difficult to choose the best solution because of the uncertainties in the definitions of the "stress" function. So, same problem, several questions : 1. Statistical consideration : With

Hi We have a few questions regarding the use of the "isoMDS" function. When we run "isoMDS" function using 60,000 x 60,000 data matrix, we get the following error message: ------------------------------------ cmdscale(d, k) : invalid value of 'n' Calls: isoMDS -> cmdscale ------------------------------------ We checked the source code of "cmdscale" and

I'm not sure this belong here... Package: MASS Version: 6.2-8 I get a core dump when I call isoMDS with an incorrect argument for y. With d as an object of class "dist": > isoMDS(d,2) Program received signal SIGSEGV, Segmentation fault. 0x40229e43 in VR_mds_init_data () at MASS.c:157 --please do not edit the information below-- Version: platform = i586-pc-linux-gnu

Hello all- I'm having some problems with memory consumption under R. I've tried increasing the appropriate memory values, but it keeps asking for more; I've even upped the heap size to 600M, significantly eating into swap (256M real, 500+M swap). So, performance slows to a crawl. What I'm trying to do is run isoMDS on a 4000x4000 matrix. My first question is, how much memory

Dear members of R-mailing list, I am using Sammon's Non-Linear Mapping in R as implemented in MASS package. I have two distance matrices (attached with the mail). For the first (/5HT_MACCS_dist.dat/) /sammon()/ works fine but for the second (/5HT_TGT_dist.dat/), I get an error message "configuration has duplicates". I checked both the matrices for duplicate values using/

Dear List: I have a question regarding an MDS procedure that I am accustomed to using. I have searched around the archives a bit and the help doc and still need a little assistance. The package isoMDS is what I need to perform the non-metric scaling, but I am working with similarity matrices, not dissimilarities. The question may end up being resolved simply. Here is a bit of substantive

I apply isoMDS to my data, but the result turns out to be bad as the stress value stays around 31! Yeah, 31 ,not 3.1... I don't know if I ignore something before recall isoMDS. My code as follow: m <- read.table("e:/tsdata.txt",header=T,sep=",") article_number <- ts(m, start = 2004,end=2008, frequency = 1 ,names=colnames(m))

Hi again Sorry, in looking again at sammon and isoMDS I see that they seem to do exactly what I want, except that they are non-metric, which means, as I understand it, that they relate the rank orders of the variables rather than the actual distances. Could I use these non-metric MDS packages even if my distances are metric? Thanks Karen -- Karen Kotschy Centre for Water in the Environment

Hi, I need math function which is used in: isoMDS, Sammon and metaMDS method. Anybody know where I may find it? Any manual or webside? I would be very happy Thanks a lot ! -- View this message in context: http://n4.nabble.com/math-function-MDS-method-tp1008294p1008294.html Sent from the R help mailing list archive at Nabble.com.

Thanks for the attention paid to my rpoblem. Please find enclosed the matrix with my dissimilarities. This is the only case in which sammon(), from the MASS package, gives me this kind of problems. Domenico > > > -----Messaggio originale----- > > Da: Jari Oksanen [mailto:jarioksa at sun3.oulu.fi] > > Inviato: mercoled?? 20 aprile 2005 11.53 > > A: Domenico Cozzetto >