similar to: cmdscale: labels missing (PR#1220)

If tbl is an object of class 'dist', you can do this: a <- sammon(tbl, k=3) But you can't do this: b <- isoMDS(tbl, k=3) Wouldn't it be sensible to have identical interfaces to sammon() and isoMDS() ? I think all that would be needed is to change this: isoMDS <- function(d, y=cmdscale(d, 2), maxit=50, trace=TRUE) { ...into this: isoMDS <-

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 using R1.7.1 on Linux, generating sammon-optimized MDS plots from distance matrices. This is a calculation I run routinely, often on sample sets of up to 100 samples. This time, with three samples, the sammon function returned an error (shown below), which I tracked down to the cmdscale function it uses to find a starting configuration. In short, cmdscale is returning NaN

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

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

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

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

I sent a query to R-Help about the availability of nonmetric multidimensional scaling (MDS) algorithms in R. I would like to thank Tony Rossini, Jonathan Baron, Sundar Dorai-Raj, and Brian Ripley for helpful replies. The gist of the replies is that isoMDS in the MASS library provides Kruskal's method for nonmetric MDS, sammon in the MASS library provides Sammon's nonlinear mapping method

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/

I have a dataframe like this (toy example): x y z "a" "a" 0 "a" "b" 1 "a" "c" 2 "b" "a" .9 "b" "b" 0 "b" "c" 1.3 "c" "a" 2.2 "c" "b" 1.1 "c" "c" 0 The observations are from a matrix like this: c 2.2 1.1 0.0 b 0.9 0.0

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

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

Full_Name: Cam Webb Version: 1.6.0 (fink X11 compile) OS: Mac OS X (Jaguar) Submission from: (NULL) (64.168.28.87) This is an unpredictable, intermittant hang during cmdscale of the mva library. Some data never cause a problem, other data always do, abut I can't track down the difference in the structure of the data. Sometimes the function will work for `difficult' data after it has

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 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

Full_Name: Laurent Gautier Version: 1.3.0-patched OS: IRIX 6.5 Submission from: (NULL) (130.225.67.199) Hello, The function La.eigen, called by cmdscale in the package mva behaves an unexplicable way (for me). The following lines show what happened. I tried the very same on linux, and it worked fine. >a <- matrix(c(1,2,3,2),3,3) >a [,1] [,2] [,3] [1,] 1 2 3 [2,]

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 >

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

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