similar to: Grid lines in cloud plot for lattice

Hi all, I seem to be having a difficult time using the 'ape' package in R when it comes to rooting trees. Here's a short screenshot: > nirK.tree Phylogenetic tree with 23 tips and 21 internal nodes. Tip labels: Burkholder, Burkholde3, Burkholde1, Burkholde4, Burkholde5, Ralstonia2, ... Node labels: , 100, 100, 100, 70, 91,... Unooted; includes branch lengths. >

Hi I am having a bit of difficulty with changing the canvas size on a trellis/lattice plot. I am plotting two "cubes" of 3-dimensional random numbers, as follows: library(gsl) library(lattice) q <- qrng_alloc(type="sobol", 3) npoints <- 200 rs <- qrng_get(q,npoints) # Plot the normal variates in a 3-dim cube p1 <- cloud(rnorm(npoints) ~ rnorm(npoints) +

Hi everyone,   I'm trying to do an Logistic Politomic Regression in R. Because I have my resposes variables and the aswer is 0 and 1 in 3 bacterial genes. Somebody know how to do this in R in a easy way?   Thank so much,   José Bustos Facultad de Ciencias Universidad Catolica Ssma. Concepcion Chile --- El lun, 31/8/09, r-help-request@r-project.org <r-help-request@r-project..org>

I don't seem to be able to put any syntax into identify() that gets it to work with "lattice" cloud() graph: layout(1) require('lattice') cloud(g3 ~ g1 + g2, data=gapp, col = "blue", xlab='G1 Score', ylab='G2 Score', zlab='G3 Score', main='3D Plot for Applicants') identify(gapp[,2:4], labels=gapp$ID) Here g1 is gapp[,2], g2

Hello, I want to do a surface plot with wireframe from the lattice package. As for now I use the following command : print(wireframe(m,main="% my title", colorkey=TRUE, col.regions=rainbow(100), drape=TRUE,aspect = c(1,1.0),ylab="y",xlab="x",zlab="z", scales=list(arrows=FALSE)),split=c(1,1,3,2), more=TRUE) How can I show the gridlines in a 3D surface

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

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.,

I'm not sure how you are incorporating time period into your data structure. Typically we are looking at plots or assemblages as the rows and taxa as the columns. Time period adds a third dimension that could be added as blocks of rows. For example, depending on the resolution of your data, one approach would be to have up to 8 rows for each locality: Loc1.1000, Loc1.2000, . . . Loc1.8000. If

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

Hi; I am working with the similarity matrix below and I would like to plot a two-dimensional MDS solution such as each point in the plot has a label. This is what I did: data <- read.table('c:/multivariate/mds/colour.txt',header=FALSE) similarity <- as.dist(data) distance <- 1-similarity result.nmds <- nmds(distance) plot(result.nmds) (nmds and plot.nmds as defined at

Hi all, I was just wondering if this is the intended behavior. Here is my setup: controller def index respond_to do |f| f.xml { render :xml => true } f.html { render :layout => :none } end end In my views I have a file for each type index.herb index.xerb The first request I send is cached and interferes with the other one. For example, if I send an xml request

Dear List, This is Elaine, a postgraduate studying in bird distributions in East Asia. I want to calculate Simpson dissimilarity index, based on a presence/absence matrix of bird species in islands in East Asia. (matrix row: 36 islands/matrix column: species ID) (R package vegan to make NMDS and R package betapart) In most papers using vegan for NMDS and betapart for dissimilarity

Hello R experts, I've used metaMDS to run NMDS on some fish abundance data, and am also working on correlating environmental data to the NMDS coordinates. I'm fairly new to metaMDS and NMDS in general, so I have what are probably some very basic questions. My fish abundance data consists of 66 sites for which up to 20 species of fish were identified and counted. I ran metaMDS on this data

I'm pleased to announce the availability of CHAN_NMS - channel driver for NMS Communications (now Dialogic) hardware. The attached README explains it all. The project website is http://chan-nms.hosting.lv/ CHAN_NMS is an Asterisk PBX channel driver that supports NMS Communications [1] (acquired by Dialogic [2]) Open Access line of products, that includes E1/T1 boards [3] for PCI(-X), PCIe,

Okay. So, after having spent quite some time never really tracking down why my package NEWS files were unacceptable to readNEWS(), I noticed that there was recent (to me anyway) development that allowed the NEWS to be done as an Rd file. Sweet! A more standard format... I converted a NEWS file in one of my unreleased packages to Rd format. checkNEWS() gave it a thumbs up. But then it went south.

Gabor, Duncan, et. al. 1. Thank you for your great comments and solutions. This is what I was hoping for! 2. Duncan: I completely agree with your criticisms. In fact, I realized the for() loop only needed the <- assignment, but your comment is important to note. However, I didn't like the for() loop either; I *much* preferred your Reduce() solution which is exactly the sort of elegant

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

As kindly pointed out to me (oh my decaying gray matter), is.object() is better suited for this test; $ svn diff src/library/base/R/diag.R Index: src/library/base/R/diag.R =================================================================== --- src/library/base/R/diag.R (revision 68345) +++ src/library/base/R/diag.R (working copy) @@ -23,9 +23,11 @@ stop("'nrow' or

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 All, I am using a Procrustes analysis to compare two NMDS ordinations for the same set of sites. One ordination is based on fish data, the other is based on invertebrate data. Ordinations were derived using metaMDS() from the {vegan} library as follows: fish.mds<-metaMDS(fish.data, distance="bray", k=3, trymax=100, wascores=TRUE, trace=TRUE, zero="add")