similar to: Question about cmdscale function

Hi. I know matrices that use distances between places works fine when using cmdscale. However, what about matricies such as: A B C D E A 0 1 23 12 9 B 1 0 10 12 3 C 23 10 0 23 4 D 12 12 23 0 21 E 9 3 4 21 0 i.e. matrices which do not represent physical distances between places (as they would not make sense for real distances such as the one above)

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

In applying multidimensional scaling, it seems to me that sometimes the underlying dimensionality of the matrix is 1. However I found a case where cmdscale failed when I tried k=1. Here it is: m<-matrix( c(.5,.81,.23,.47,.61, .19,.5,.06,.17,.28, .77,.94,.5,.74,.85, .53,.83,.26,.5,.64, .39,.72,.15,.36,.5), nrow=5) # BTW I think cmdscale uses only the lower triangle--how to enter only # that

Dear R developers, there appears to be a small problem with function cmdscale: for non-Euclidean distance matrices, using option add=FALSE (the default), cmdscale misses the smallest eigenvalue. This affects GOF statistic g.1 (See Mardia, Kent + Bibby (1979): Multivariate Analysis, eq. (14.4.7). The corresponding formula in Cox + Cox (2001): Multidimensional Scaling, 2nd ed., p 38, would

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.

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 looking for someone to explain the difference between these procedures. The function prcomp() does principal components anaylsis, and the function cmdscale() does classical multi-dimensional scaling (also called principal coordinates analysis). My confusion stems from the fact that they give very similar results: my.d <- matrix(rnorm(50), ncol=5) rownames(my.d) <-

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

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 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

The function cmdscale tries to copy names from the source to the result. This only works if the source is a matrix. If m is a matrix with labels (rownames) and d is an object of class "dist" with labels, this works: cmdscale(m) ...but with this, there are no labels in the results: cmdscale(d) However, this works: cmdscale(as.matrix(d)) My suggestion is to change, in

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

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,]

Dear All, I would like to ask how to customize the graph corresponding to a procrustes analysis. I have to distance matrices, that I transform to two set of coordinates by means of muti dimensional scaling: library(mva) c1<-cmdscale(mat.dist1) c2<-cmdscale(mat.dist2) I vant to rotate c2 on c1, and I use the "procrustes" analysis from the {vegan} library. library(vegan)

Dear R developers, I am visualising high dimensional genomic data and for this purpose I need to compute pairwise distances between many points in a high-dimensional space (say I have a matrix of 5,000 rows and 20,000 columns, so the result is a 5,000x5,000 matrix or it's upper diagonal).Computing such thing in R takes many hours (I am doing this on a Linux server with more than 100 GB of RAM,

I'm using the WINDOWS 95 version of R (with midified menu "exe.zip"): I tried to do library(mva) data(quakes) quakes<-quakes[sample(seq(1:1000),100),1:5] cmd.dsq<-cmdscale(dsq) Error in .C("dblcen", x, as.integer(n)) : C/Fortran function not in load table how can I solve this problem? -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

I'm using rseptbeta for w95, I tried to do: library(mva) data(quakes) quakes<-quakes[sample(seq(1:1000),100),1:5] cmd.dsq<-cmdscale(dsq) Error in .C("dblcen", x, as.integer(n)) : C/Fortran function not in load table how can I solve this problem? Andrea Rossetti _______________________________________________________ Statistica & Informatica per la Gestione delle Imprese

I'm using rseptbeta for w95, I tried to do: > library(mva) > data(eurodist) > cmdscale(eurodist) Error in .C("dblcen", x, as.integer(n)) : C/Fortran function not in load table > how can I solve this problem? Andrea Rossetti _______________________________________________________ Statistica & Informatica per la Gestione delle Imprese | Universit? degli Studi di

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/