similar to: results from sammon()

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 >

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

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 <-

R-help, Is there any package/function in R which can perform multi-dimensional scaling? Thank you in advance

Hello I will be applying MDS (actually Isomap) to make a psychological "concept map" of the similarities between N concepts. I would like to scale to a large number of concepts, however, the resulting N*(N-1) pairwise similarities is prohibitive for a user survey. I'm thinking of giving people random subsets of the pairwise similarities. Does anyone have recommendations for this

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've been unable to find a R package that provides the means of performing Clarke & Ainsworth's BIO-ENV procedure or something comparable. Briefly, they describe a method for comparing two separate sample ordinations, one from species data and the second from environmental data. The analysis includes selection of the 'best' subset of environmental variables for explaining

I'm looking to switch to Mac platform. Anyone had any experience with that? I'm expecting on a power G4 laptop later this week.... hope R behaves... -- dok

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

Dear all, I didn't find any graphical solution in the package "mva" to plot the canonical scores from a CCA (canonical correlation analysis). Does anybody knows how to plot or has anybody already programmed : - the map of the canonical scores, - the graph of the canonical weights, - the correlation circle i.e. the canonical loadings ? Thank you for help ...

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

Colleagues, I'm developing a library of functions for community ecology analyses and have a couple of questions that I've not been able to answer via faqs or docs. 1) Are there existing functions for: a) Bray-Curtis (polar) ordination? b) non-metric multidimensional scaling (NMDS)? c) canonical correlation analyses (CCA and DCA)? d) TWINSPAN (doubtful...)? 2) If not,

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

Dear all, I'd like to get a linear regression of some data, and impose that the line goes through a given point P. I've tried to use the lm() method in the package "stats", but I wasn't able to specify the coordinates of the point P. Maybe I should use another method? I also have another question: How does lm() choose the point through which the output straight line goes in

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.

hi, my attempt to install the package Hmisc v3.0-1 fails with the message: /usr/bin/ld: cannot find -lfrtbegin collect2: ld returned 1 exit status make: *** [Hmisc.so] Error 1 ERROR: compilation failed for package 'Hmisc' i'm at a loss here. any hints will be very much appreciated. i'm running: debian stable R version 2.0.1 gcc 2.95.4-14 g77 2.95.4-14 binutils 2.12.90.0.1-4

Is there an R function that does canonical correspondence analysis. Can it be done using the VR function corresp()? If not, how hard it be to write R code to do it? I am a population biologist with long but patchy programming experience in C, Smalltalk, Java and other languages. Thanks, Patrick Foley patfoley at csus.edu

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

When I try to run the "sammon" function of the multiv package, I always get this error message: Error in as.vector(dist(a)) : couldn't find function "dist" It happens even with example(sammon). I am running R 1.5.0 on Win98 and I have still installed R 1.4.1 but it doesn't work on the old R version with the older multiv package either. Is there a problem with the

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