similar to: isoMDS vs. other non-metric non-R routines

Hello everyone, I have a question on isoMDS. My data set (of vegetation) with 210 samples is in this way: Rotfoehrenau Lavendelweidenau Silberweidenau .... 067_Breg.7 0 2 0 .... 071_Dona.4 0 2 6 .... ... I want to do an isoMDS-analysis with the dissimilarity index

Dear all, I'm running a set of nonparametric MDS analyses, using a wrapper for isoMDS, on a 800x800 distance matrix. I noticed that setting the parameter k to larger numbers seriously increases the calculation time. Actually, with k=10 it calculates already longer than for k=2 and k=5 together. It's now calculating for 6 hours, and counting... There is quite a difference between the

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 I have just (finally) started to poke around in R and wanted to analyse a stream fish dataset with 28 sites and 18 species. When trying to follow the Vegan manual to run nmds from distance measures calculated by the vegdist function it turns out that I have two sites (streams) with the exactly the same four species (I have used pres-abs data in this case). When I try to run isoMDS I get an

Hi; I am working with the similarity matrix below and I would like to plot a two-dimensional MDS solution such as each point in the plot has a label. This is what I did: data <- read.table('c:/multivariate/mds/colour.txt',header=FALSE) similarity <- as.dist(data) distance <- 1-similarity result.nmds <- nmds(distance) plot(result.nmds) (nmds and plot.nmds as defined at

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 <-

Hello This is a simple question but I couldn't google an answer. In the procrustes function of the vegan package, one uses plot(procrustes_object, kind=2) to obtain a plot of the residual differences. For instance: data(varespec) vare.dist <- vegdist(wisconsin(varespec)) library(MASS) mds.null <- isoMDS(vare.dist, tol=1e-7) mds.alt <- isoMDS(vare.dist,

hello, subsequently to a NMDS analysis (performed with metaMDS or isoMDS) is it possible to rotate the axis through a varimax-rotation? Thanks in advance. Bernd Panassiti

Dear R-helpers, I am running metaMDS in the vegan package, which uses isoMDS in MASS, to perform Nonmetric Multidimentional Scaling (NMDS). I have seen some authors report a p-value for the NMDS ordination based on randomization of the dataset. As I understand it this is meant to compare the stress in your dataset to multiple runs of randomized data. I do not see a way to perform such a test in

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 using vegan to do an NMDS plot and I would like to suppress the labels for the loading vectors. Is this possible? Alternatively, how can I avoid overlap? Many thanks for the help. Example code: #perform NMDS using metaMDS() function spe.nmds<-metaMDS(data, distance='bray',k=2 , engine = "isoMDS", autotransform=F, trymax=1000) #calculate the loading (i.e.,

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

Hi, For example: I built a half matrix "w" using a daisy(x, metric = c("euclidean")) http://www.nabble.com/file/p25211016/1.jpg And next I transformed this matrix "w" using isoMDS function, for example isoMDS(w, k=2) and as result I got: http://www.nabble.com/file/p25211016/2.jpg And now I have two questions: 1. If number in matrix w[2, 1] (= 0.41538462) match

Hello everyone! metaMDS(cm, distance = "euclidean", k = 2, trymax = 50, autotransform =TRUE, trace = 1, plot = T) (cm is a similarity matrix, in which values are positive integers or 0) I use this command to run NMDS on my matrix "cm". But the stress is very high after analysis. About 14. Actually, there is no improvment comparing with using isoMDS.

I am starting with a matrix in which rows are vegetation plots and columns are various characteristics including ID# and elevation. I removed elevation and ID columns to avoid having those characteristics influence the distances between points which I calculated using the "dist" command. The resulting distance file was then used in isoMDS. What I want to know is whether I can

When I type "isoMDS()" in the R environment, a error shows up: no such function "isoMDS". Why? And what should I do to use isoMDS? Additionally, I cannot install add-on packages. Typing "Rcmd.exe INSTALL e:/VR_7.2-44.zip" results in "'perl' is neither command nor executable file...". Why this happens?Thanks. The setup file I downloaded is

Hi, I am currently working on some data and feel that NMDS would return an excellent result. With my current data set however I have been experiencing some problems and cannot carry out metaMDS. I have tried with a few smaller data sets which I created for practice sake and this has worked fine. I think it is the set up of my data set that is causing me trouble. I have 18 columns and 18 rows,

Hi all, I try to calculate the stress of a configuration using the formula in the isoMDS help, but I don't have the same result than the stress returned by isoMDS : > library(mva) > library(MASS) > data(swiss) > swiss.x <- as.matrix(swiss[,-1]) > swiss.dist <- dist(swiss.x) > swiss.mds <- isoMDS(swiss.dist) initial value 2.979731 iter 5 value 2.431486 iter 10

Dear List, I am writing a custom panel function and xyplot method to plot the results of a procrustes analysis from the vegan package. I am having trouble getting the call to panel.arrows to work as I wish when conditioning. The attached file contains the function definitions for the xyplot method and the custom panel and prepanel functions I am using. This example, using data and functions from

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