similar to: Cluster Analysis with flexible beta linkage method

Dear All I am trying to do a partial canonical analysis of principal coordinates using Bray-Curtis distances. The capscale addin to R appears to be the only way of doing it, however, when I try and calculate a Bray-Curtis distance matrix either using Capscale or Vegedist (capscale I understand uses Vegedist anyway to calculate its distance matrix), R uses up all available memory on the computer,

I have tried without success to find a way including the square root symbol in lattice strips as part of my conditioning labels. I have tried supplementing by creating a list of vectors using the var.name function coupled with the expression function used in xlab/ylab. xyplot(adjusted_Rand_index~cluster|distance_measure, main="Level of agreement between partitions: Wards Method",

I have 4 very large species lists and I would like to compare them. I have the following results from running Sorenson’s dissimilarity tests: Norfolk Fens compared to Suffolk Coastal Fens: QS=0.583961142689298 Norfolk Fens compared to Breckland Edge Fens: QS=0.714896020281379 Norfolk Fens compared to Other Fens:

Dear all, I am having a little trouble deciphering how to change the default x-axis labels in a lattice xyplot (or any type of lattice plot for that matter). I have tried using the "demo("labels") function but the code is truncated at precisely the wrong moment! All I am trying to do is to add superscript to two of the labels for which i tried using the expression function. It

Does R have a function to calculate Bray-Curtis distance measures, which is probably one of the most frequently used and recommended dissimilarity measures in ecology? It isn't mentioned in dist().

How to calculate sorensen (bray-curtis) distance by dist function within the vegan package? Cheers Duccio

I have tried without success to find a way including the square root symbol in lattice strips as part of my conditioning labels. I have tried supplementing by creating a list of vectors using the var.name function coupled with the expression function used in xlab/ylab. xyplot(adjusted_Rand_index~cluster|distance_measure, main="Level of agreement between partitions: Wards Method",

Dear R-help, We are conducting a distance-based redundancy analysis using capscale and then testing for statistical significance for six terms in the model for the constrained ordination using anova.cca in the vegan package. The significance test is sequential, i.e., testing for significance of a term only after accounting for all preceding terms. Could someone please provide us with either the

I'm getting lots of grief from reviewers about figures generated with the envfit function in the Vegan package. Has anyone else struggled to effectively explain this analysis? If so, can you share any helpful tips? The most recent comment I've gotten back: "What this shows is which NMDS axis separates the communities, not the relationship between the edaphic factor and the

#Hi, I am trying to run an MRPP with community data (spp-site-matrix). I use the following code: mzbtaxa_mrpp <- mrpp(mzbdist,mzbsites$Site) #mzbdist being a distance object (Bray-Curtis similarity matrix) derived from my sqrt transformed community data set, created with function 'vegdist', mzbsites$Site refers to factors structuring my community. #when I run this code, I get the

Hi, I'm trying to use metaMDS with a dissimilarity matrix of angles, not Bray-Curtis, and I wanted to know if there is an in-built function to produce a plot of stress values against dimensions, that could be used to determine the 'true' dimension of the solution. The number of objects is only a lowly 8 so any solution higher than 2-dimensional is not likely to be interpretable,

Dear all: I want to ask question about "binary" distance measure. As far as I know, there are many binary distance measures,eg, binary Jarcad distance, binary euclidean distance, and binary Bray-Curtis distance,etc. It is even more confusing because many have more than one name. So , I wan to know what the definite name of the binary distance measure of the "dist" function

Hi, forgive me if someone has already posted about this but I have had a look and cannot find the answer, also I am very new to R and been getting the grips with this. I have been trying to use Adonis to find out if there are significant difference between groups on data that I have analyses with NMDS, and have been struggling with getting this to work and understanding what is going on. I am

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

Hi R experts, I'm attempting to run Linear Discriminant Analysis using the lda function in the MASS package. I've got around 50 predictor variables and one response variable. My response variable has 5 numeric categories that represent different clusters of fish abundance data (clusters were developed using Bray-Curtis and NMDS), and my predictor variables are environmental variables that

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 Folks, I'm hoping someone could help me a bit. I have plotted the following: ########################################### tiff("plot7.tiff",units="cm",width=15,height=36,res=700) layout(matrix(c(1,2,3,4,5,6),3,1),widths=lcm(c(15)),heights=lcm(c(12,12,12)),respect=TRUE) plot.t1<-plot(data.dist,flot1.bray.hell,xlab="",ylab="Bray-Curtis dissimilarity

I'm having trouble with the ordisurf function in the vegan package. I have created an ordination plot (cmdscale) of 60 samples based on Bray-Curtis dissimilarities, and would like to overlay various soil edaphic characteristics as possible clues to the clustering I observe in my plot. However, I find that ordisurf creates a surface on the plot that is a perfect, even gradient - and

Dear R-listers, Is anyone familiar with a package that would perform bootstrapping on species/site matrices for clustering ? So far I have been using the vegan package to generate trees (Bray-Curtis index), but I would like to associate a certainty to each node (similarly to a phylogenetic tree). If no package exist, I would know how to generate bootstrapped matrices of distance, but how

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