similar to: interpretation of stress in NMDS

Hello, I can draw a basic stress plot for NMDS with the following code in package Vegan. > stressplot(parth.mds, parth.dis) When I try to specify the line and point types, it gives me error message. > stressplot(parth.mds, parth.dis, pch=1, p.col="gray", lwd=2, l.col="red") Error in plot.xy(xy, type, ...) : invalid plot type In the above code, if I removed line type,

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

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.

hello, i'd like to extract values from stressplot, but as this should happen within a long run of code, which also does a multiple plot, i need to prevent stressplot to print to the device. i tried ..,plot=F), but this is useless. any advise on this? thanks, kay ----- ------------------------ Kay Cichini Postgraduate student Institute of Botany Univ. of Innsbruck

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, I'm using nmds command (library vegan) to analyze some fishing data. I'd like to plot not only points, but also the names of species and stations in a specified position. I used the command text(nmds$points[,1], nmds $points[,2],labels=row.names(nmds $points),pos=3,cex=0.5) But the labels are sometimes overlapped. Is there any way to use identify, or a similar command, to plot 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

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

If you submit these lines, you end up with variable "vare.dis". I want to export vare.dis to csv. Stuck I am. library(vegan,logical.return = TRUE) #return=true verifies package is available library(MASS,logical.return=TRUE) #return=true verifies package is available data(varespec) #varespec is an example data file in the vegan package vare.dis <- vegdist(varespec)

Hello, We are trying to find a function to compute "stress" in our multidimensional scaling analysis of a dissimilarity matrix. We've used "dist()" to create the matrix and "cmdscale()" for the scaling. In order to determine the number of dimensions we would like to plot stress vs. dimensions. However, we cannot find a pre-made command. It seems that other

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

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.

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 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

Dear All, I was wondering whether anyone might be able to provide some advice with an nMDS / R problem. I?m trying to run nMDS on a dataset that contains many missing values and was wondering how I can account for the missing values when running nMDS? It seems as though the data are being grouped depending on where the zero values appear. Any suggestions greatly appreciated. Thank you very much

Dear r-helpers! How can I integrate other distances (in the form of a dist object) into function metaMDS? The problem: metaMDS needs the original data.frame for the calculation and only the default distances of function vegdist are allowed. Any suggestions are greatly appreciated! Thank you, Kim -- Jetzt kostenlos herunterladen: Internet Explorer 8 und Mozilla Firefox 3.5 - sicherer, schneller

Hi, I am stuck in one problem when doing nonmetric multidimensional scaling. I use the function 'metaMDS' in the package 'vegan' to work on the presence/absence community data. The problem is when two samples are identical (dissimilarity = 0), metaMDS cannot work with zero dissimilarity. I don't want to delete the duplicates as they are true samples from different locations.

Hi! Thanks for providing great help in R-related statistics. Now, however I'm stuck. I'm not a statistics person but I was recommended to use R to perform a nmds plot and PerMANOVA of my dataset. Sample(treatment) in the columns and species (OTU) in the rows. I have 4 treatments (Ambient Temperature, Ambient temperature+Low pH, High temperature, High temperature+low pH), and I have 16

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

Dr. Stevens, Hi, my name is Trey Scott, and I'm a grad student of Brian McCarthy's. He referred me to you because of your expertise in handling complex R problems. We were hoping you could help us solve a nagging problem that is prohibiting me from producing graphicl output. Here is a simple mock-up of the matrix I'm using a b c d e f 1i 1 4