[R] null model for a single species?

Dear List members, I would like to test whether an observed occupancy of lakes in a landscape has occurred randomly (by chance) or not. How can I do that? The problem is that it concerns only a single species and I would like to use binary data only. At first I thought of generating null

[R] ctc package

Dear R-helpers, I would like to export hierarchical clusters e.g. fit - hclust(d, method=ward) in the newick format write(hc2Newick(fit),file='hclust.newick') Searching for a possibility I found this solution in the package ctc (http://www.bioconductor.org/packages/bioc/html/ctc.html).

[R] triangular plot

Sorry for probably again an easy question but I can not find the solution... Using the ade4 package I am drawing a triangular graph: triangle.plot(data2, label = row.names(data2), clab=0.6, show.position=FALSE, box=FALSE) Which is what I want. Unfortunately the labels have a frame and a white

Re: [R] ctc package

Dear Allan, Thank you very much! Sometimes the forest is difficult to see when you are looking at the trees only... as we would say... With kind regards Johannes __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE

[R] dimnames does not match array extent

Dear R help-list, I am trying to calculate Monmoniers algorithm. I have 3 data sets: coordinates (coord), distance matrix (comdist) and geographical distance matrix (geodist). I consistently get the error dimnames does not match array extent. However, when I use the function structure I get

[R] consensus clusterings

Dear all, does anybody know a package or solution which incorporated one of the three algorithms to build consensus clusters, proposed by Nguyen Caruana: - iterative voting consensus (ivc) - iterative probabilistic voting consensus (ipvc) - iterative pairwise consensus (ipc) Thanks in advance.

[R] using multiple matrices

Dear R-list, another question trying to build consensus cluster ;-) Using the package clue I have found a method of building consensus clusters the following way from one distance matrix: clust1 - c(ward, single, complete, average, mcquitty, median, centroid) clust_res - lapply(clust1,

[R] name siz ein cluster

I would like to change to size of the names in a cluster dendrogram (not the axis or the header) (package clue). The normal things (pch, cex.label, font) do not work here. Thanks in advance! Johannes __ R-help@r-project.org mailing list

Re: [R] name siz ein cluster

2093 8565 http://www.biota-africa.org http://community-ecology.biozentrum.uni-wuerzburg.de -Ursprüngliche Nachricht- Von: Simon Pickett [mailto:simon.pick...@bto.org] Gesendet: Mittwoch, 13. Mai 2009 16:30 An: Penner, Johannes; r-help@r-project.org Betreff: Re: [R] name siz ein cluster I'm

[R] dimnames do not match array extent

Dear adegenet users, I am trying to calculate geographical barriers using monmonier. However, I consistently get the error dimnames do not match array extent. - import of the distance matrix: read.table - conversion 1: as.dist(data, diag=TRUE, upper =TRUE) - conversion 2: as.matrix(data) -

[R] cn is not a nb object

Dear all, I am trying to calculate barriers with the monmonier algorithm (adegenet). mon1 - monmonier(mycoordinates, mydistancamatrix, network$cn, ...) The network beforehand looked alright. However, I always get the error: cn is not a nb object. I am not really sure what this means, probably

[R] graph with 15 combinations

Dear R helpers, I have a data set with 4 types (W, C, E S). Now I have values for all types plus all possible combinations (the order is unimportant): W, C, WC, E, WE, CE, WCE, S, WS, CS, WCS, ES, WES, CES WCES. Ideally I would like to represent everything in one graph and as concise as

Re: [R] graph with 15 combinations

://community-ecology.biozentrum.uni-wuerzburg.de -Ursprüngliche Nachricht- Von: Greg Snow [mailto:greg.s...@imail.org] Gesendet: Montag, 20. April 2009 21:30 An: Penner, Johannes; r-help@r-project.org Betreff: RE: graph with 15 combinations http://en.wikipedia.org/wiki/Venn_Diagram

[R] chaining consensus in cluster analyses

Dear R-helpers, conducting different community ecology analyses my main aim is to find groupings in the data and geographical borders between communities and to prove them statistically. So after conducting a global test (Mantel) I am running a NMS and cluster analyses. These are followed by