similar to: Problem with Species x Site matrix please help

am at my wit's end. I am not sure what is wrong with this data matrix. It is sparse because it is a matrix of species, but I have looked at the row totals and column totals and they are positive. rmetaMDS(x.d) Error in if (autotransform && xam > 50) { : missing value where TRUE/FALSE needed What is wrong? And in the future how in God's name do I easily diagnose whatever

Hi, I've been using R for a while now but I've got a problem with metaMDS (in the vegan package) that I can't quite figure out. I have a set of proportion data (from 0-1, rows sum to 1) that I apply metaMDS to using the command: nMDS.set=metaMDS(sqrt(test.set),distance="euclidean",k=3,zerodist="add",autotransform=FALSE) I am using a squared-chord distance

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,

Greetings everyone, I am running MDS on a very large dataset (12 x 25071 - 12 model runs with 25071 output values each), and also on a very much reduced version of the dataset (randomly select 1000 of the 25071 output values). I would like to look at similarities/dissimilarities between the 12 model runs. When I use metaMDS on the full dataset, I get a warning message: Warning message: In

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.,

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.

Hi, First I should note I am relatively new to R so I would appreciate answers that take this into account. I am trying to perform an MDS ordination using the function ?metaMDS? of the ?vegan? package. I want to ordinate species according to a set of functional traits. ?Species? here refers to ?sites? in traditional vegetation analyses while ?traits? here correspond to ?species? in such

Hi R-experts, I am using the envfit function over an ordination of floristic data. The problem is that every time that I run it changes the results. Sometimes dramatically, selecting variables that the first time were not significant. I do not get what could be the problem or if is normal given the permutations are different. # the NMDS ordination gap_flor_NMDS_chord <- metaMDS(gaps_flor,

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.

Hi, I am trying to create 3 mds plots: one with axis 1 vs axis 2, one with axis 2 vs axis 3, and one with axis 1 vs axis 3. When inputting my code, I only end up with one diagram and when inputting mdsg.mds$dims, the program returns 2 for 2 dimensions. How can I create the other two plots? Any help would be greatly appreciated, Calla Carbone The table I use is number of each taxa on each

Dear all, I'm analyzing a dataset (A) of 400 cases with 11 binary variables. Unfortunately, several (actually a lot) of cases are identical. NA are also present. I want to to plot distances between cases. For this, I obtained a distance matrix by dist(A, method="binary"). I then analyzed the obtained distance via Principal coordinate analysis with cmdscale(). Results are fine.

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

Hi, I am working with a species-by-trait .csv file (columns=traits, rows=species) and get the following warning message when trying to plot results of both metaMDS and pcoa:  "Warning message: In ordiplot(x, choices = choices, type = type, display = display,  :   Species scores not available" I am using a Gower's transformation in both procedures within the metaMDS or pcoa

The design decision in metaMDS says that it uses: Minchin, P.R. (1987) An evaluation of relative robustness of techniques for ecological ordinations. Vegetatio 71, 145-156. This is the paper that I found by the same name. Is this the correct reference? Minchin, Peter R.1987. An Evaluation of the Relative Robustness of Techniques for Ecological Ordination. Vegetatio. Vol. 69, No. 1/3: 89-107.

My question is with respect to mCLUST and the values of BIC and log likelihood. The relevant part of my R script is: ######################### BEGIN MDS ANALYSIS ######################### #load data data <- read.table("Ecoli33_Barry.dis", header = TRUE, row.names = 1) #perform MDS Scaling mds <- metaMDS(data, k = Dimensions, trymax = 20, autotransform =TRUE, noshare = 0.1,

I am using the function metaMDS with jaccard distances to ordinate a set of constituent by site matrix. I can post this data if it would be helpful, but it is large to include in an email. I can also provide reproducable code if necessary. I would like to get an R^2 value for the axes of the ordination configuration that I get with metaMDS in the vegan package is there a way to do this- is it

I am trying to plot an nMDS plot using ggplot2. My rownames are coded so that they can be broken down by Site, Species, Treatment, or Replicate based on unique separators. There are no column headers. I am having trouble coding ggplot2 to plot by Site -or- Species -or- Treatment and NOT by all unique row names. This is probably a simple question but I'm still very new with command line

row <- c("a","b","c","d","e","f","g") #rows from larger data frame row.1 <- c("a","b","c","g") #rows of smaller data frame because d, e, and f don't contain any of the species, but the zeros are important x <- data.frame(sp1=rnorm(4), sp2=rnorm(4), sp3=rnorm(4),

hello all; one colleague found a strange behavior, that can be annoying : -bash-3.1$ telnet 0 143 Trying 0.0.0.0... Connected to 0 (0.0.0.0). Escape character is '^]'. * OK [CAPABILITY IMAP4rev1 LITERAL+ SASL-IR LOGIN-REFERRALS ID ENABLE AUTH=PLAIN AUTH=CRAM-MD5] Dovecot ready. l login login pass l OK [CAPABILITY IMAP4rev1 LITERAL+ SASL-IR LOGIN-REFERRALS ID ENABLE SORT SORT=DISPLAY

I have looked all over the internet for being able to color sites differently in a plot of an MDS (metaMDS)- I would like to color the different sites in the ordination plot (plot or ordiplot). I have set the matrix up so that my site code is 1 .... 296 (first column). is there a way to make 1-23 blue, 24-40 red etc. thanks Stephen -- Let's not spend our time and resources thinking