similar to: Clustering analysis with ordination plots

Hi all, I have site data with plant species cover and am looking for trends. I'm kind of new to this, but have done lots of reading and can't find an answer. I tried decorana (I know it's been replaced by ca.) and see a trend, but I'm not sure what it means. Is there a way to get the loadings/eigenvectors of the axes (like in PCA)? Is there a way to do this with rda() too? How

Hello, I am trying to learn how to do PCA. I found a tutorial online, but what I'm seeing in my installation does not match what is in the tutorial. Specifically, if I select Statistics:Dimensional Analysis: Principal-components analysis, the dialog I am presented with does not include an option to create an ordination plot. My question is why not? Is this a problem with my data set,

hello all R experts, how do I calculate the reliability between the two groups using the ICCs? I'll appreciate your reply, Thanks Sincerely, Supreet kaur, Biomedical research engineer, Nationwide Childrens Hospital, Columbus, OH (614)355-3509 [[alternative HTML version deleted]]

Hi all, I am using the vegan package to run a prcincipal components analysis on forest structural variables (tree density, basal area, average height, regeneration density) in R. However, I could not find out how to extract factor loadings (correlations of each variable with each pca axis), as is straightforwar in princomp. Do anyone know how to do that? Moreover, do anyone knows

Hi Listers, I am trying to reflect a PCA biplot in the x-axis (i.e. PC1) but am not having much success. In theory I believe all I need to do is multiply the site and species scores for the PC1 by -1, which would effectively flip the biplot. I am creating a blank plot using the plot command and accessing the results from a call to rda. I then use the calls to scores to obtain separate site and

Dear friends, I am beginning to use R software in my academic research and I'm having some problems regarding the use of PCA. I have a table with 24445 rows and 9 columns, and I used the function prcomp() to do the analysis. Working with an example?: x<-read.table("test.txt", header=T) row.names(x)<-x[,1] x<-x[,-1] require(stats) pca<-prcomp(x, scale=T) names(pca) ##

Hi, I have a problem with making PCA plots that are readable. I would like to set different sympols instead of the numbers of my samples or their names, that I get plotted (xlabs). How is this possible? With points, i don´t seem to get the right data plotted onto the PCA plot, as I do not quite understand from where it is taken. I dont know how to plot the correct columns of the prcomp

Hi All, Can anyone point me a hint (package) how to draw a 3D plot using the first 3 components from PCA? Thanks a lot, FD [[alternative HTML version deleted]]

Hello, supposing that I have two or three clear categories for my data, lets say pet preferece across fish, cat, dog. Lets say most people rate their preference as being mostly one of the categories. I want to do pca on the data to see three 'groups' of people, one group for fish, one for cat and one for dog. I would like to see the odd person who likes both or all three in the

G'Day R users! Following an ordination using prcomp, I'd like to test which variables singnificantly contribute to a principal component. There is a method suggested by Peres-Neto and al. 2003. Ecology 84:2347-2363 called "bootstrapped eigenvector". It was asked for that in this forum in January 2005 by J?r?me Lema?tre: "1) Resample 1000 times with replacement entire

Dear R community In a current paper, I'm (briefly) considering the topic of producing scatterplots or maps with point labels positioned in such a way as to minimize label overlap and occlusion. This is a topic with a large, but scattered literature. In CS, it is considered NP-hard, but there are a variety of approximate solutions. The most complete bibliography I've found is the

So far, those look the same client: [root at mseas FixOwn]# getfacl /gdata/bibliography/Work/GroupBib/trunk/ getfacl: Removing leading '/' from absolute path names # file: gdata/bibliography/Work/GroupBib/trunk/ # owner: phaley # group: mseasweb # flags: -s- user::rwx group::rwx other::r-x server: [root at mseas-data2 ~]# getfacl /gdata/bibliography/Work/GroupBib/trunk/ getfacl:

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

I am severely rusty re. multivariate / ordination analysis, having done my last work 40 years ago (in plant ecology). I am interested in exploring applications of multivariate analytic approaches to data from the history of motion picture films. I'd very much appreciate any pointers as to possibly appropriate proceedures. The individual "samples" may be individual films and the

Hi We have just migrated our data to a new file server (more space, old server was showing its age). We have a volume for collaborative use, based on group membership. In our new server, the group write permissions are not being respected (e.g. the owner of a directory can still write to that directory but any other member of the associated group cannot, even though the directory clearly

Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: 7bit X-Virus-Scanned: by amavisd-new X-Spam-Checker-Version: SpamAssassin 2.63 (2004-01-11) on hypatia.math.ethz.ch X-Spam-Level: **** X-Spam-Status: No, hits=4.2 required=5.0 tests=MSGID_FROM_MTA_HEADER,RCVD_IN_BL_SPAMCOP_NET autolearn=no version=2.63 Dear r-help list, my question is about ordination technics:

I know this question is very simple, but I am not figure it out I have the data frame:   test<- data.frame(year=c(2000,2000,2001,2001),x=c(54,41,90,15), y=c(29,2,92,22), z=c(26,68,46,51)) test   year    x   y   z 1 2000 54 29 26 2 2000 41  2  68 3 2001 90 92 46 4 2001 15 22 51   I want to sum the vectors x, y and z within each year (2000

Hi Im currently trying to plot my NMDS data together with fitted variables (envfit funct) on an ordination plot. The plot function shows two displays="sites" and "sp". I was wondering how to plot it so that the sites come up as different points for different sites but the species come up as actual names? It looks a little busy at the moment with everything in. Sya -- View

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R community: I would like to add a new title to the bibliography on the R website (http://www.r-project.org/doc/bib/R-books.html), but I cannot find instructions for doing that. Can anyone tell me, whom should I contact in order to add a new book? (I added the title to the wiki's list of books, but the bibliography and the list don't seem to be connected.) Thank you! Paul Paul