similar to: What is the formula of Pseudo-F statistic in capscale in vegan?

Hi list, I am using the capscale function in vegan_2.0-7 to do a constrained principal coordinates analysis, and I kept getting the following error message: Error in Y.r[, oo, drop = FALSE] : subscript out of bounds I googled but I couldn't find an answer. Could anyone tell me why this error msg and what to do? Here is the command I used:

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,

Hi, I'm a beginner with R, but I'm getting excellent results with it. Well I've got an capscale object (vegan package) and I want to made a biplot with symbols representing six groups of areas. With the plot.cca function and some par attributes (like 'labels') I was able to substitute the samples names for keyboard symbols ('x','o','#',ect), but

Hello, I am interested in using the capscale function of vegan package of R. I already have a dissimilarity matrix and I am intended to use it as 'distance' argument. But then, I don't know what kind of data must be in 'comm' argument. I don't understand what type of data must be referred as 'species scores' and 'community data frame' since my data refer to

Hi, I'm a beginner with R, but I'm getting excellent results with it. Well I've got an capscale object (vegan package) and I want to made a biplot with symbols representing six groups of areas. With the plot.cca function and some par attributes (like 'labels') I was able to substitute the samples names for keyboard symbols ('x','o','#',ect), but it's

Hello there! I am still struggling with a binomial response over all categorical variables (some of them with 3 levels, most with 2 levels). After initial struggles with glm's (struggle coming from the data, not the actual analysis) I have decided to prefer contingency tables. I have my data such as: response:

I'm working with capscale and permutest for the first time, and having trouble getting statistical analyses for more than one constraining variable. I've read the documentation, but setting first=FALSE or using by="axis" doesn't seem to be helping. capscale seems to be fine, I receive output for more than one constrained axis. What am I doing wrong?

I am trying to use the cca/rda/capscale functions in vegan to analyse genetic distance data ( provided as a dist object calculated using dist.genpop in package adegenet) with geographic distance partialled out ( provided as a distance object using dist function in veganthis method is attempting to follow the method used by Geffen et al 2004 as suggested by Legendre and . FORTIN (2010). I

Hello! I am eager to learn if I only have a data about the relationship between otu and sample, could I use the function capscale, and final make a point plot that x-axis is CAP1 and y-axis is CAP2? Besides, what function could I use to make the different rarefaction curve with different color in the a plot in R? Appreciate very much.

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

Say I have the following program and dwarf line number table. Program: kernel void nbt03( global uint *ip ) { size_t groupSize = get_local_size(0); for (int i=0; i < 256; ++i) { *ip += groupSize; } } Line Number Statements: Extended opcode 2: set Address to 0x38 Special opcode 6: advance Address by 0 to 0x38 and Line by 1 to 2 Set column to 40 Extended opcode 2: set

Hi, my x-axis contains labels that consist of two lines (the actual label and below information about groupsize). Unfortunately, there is too little spacing between labels and tickmarks in this situation. Is there a parameter to tune spacing between axis and labels? Thanks, Chris

Hi everybody, I'm trying, without success, to avoid some variables labels to overlap on a capscale (vegan package) object graph. I was able to move the labels with the coding below, but it moves the entire vector... CAPobj<-CAPpotiFT for(i in c(2:8))CAPobj$CCA[[i]][,1]<-CAPpotiFTI$CCA[[i]][,1] CAPpotiFTI$CCA[[i]][,1][2]<-0.85 And here the graphic script

How should I analysis it in R ???? all the resposes variables are ordinal from 0 to 10. and the explanatory variable is a factor ... -- View this message in context: http://old.nabble.com/Multivariate-problems-.-.-.-with-200-resposes-variables-and-1-explanatory-variable-tp26522912p26522912.html Sent from the R help mailing list archive at Nabble.com.

From: Matthew Wilcox <mawilcox at microsoft.com> The sbitmap and the percpu_ida perform essentially the same task, allocating tags for commands. Since the sbitmap is more used than the percpu_ida, convert the percpu_ida users to the sbitmap API. Signed-off-by: Matthew Wilcox <mawilcox at microsoft.com> --- drivers/scsi/qla2xxx/qla_target.c | 16 ++++++-----

Dear r-Community, Step1: I would like to calculate a NMDS (package vegan, function metaMDS) with species data. Step2: Then I want to plot environmental variables over it, using function envfit. The Problem: One of these environmental variables is cos(EXPOSURE). But for flat releves there is no exposure. The value is missing and I can't call it 0 as 0 stands for east and west. Therefore I

Removing the percpu_ida code nets over 400 lines of removal. It's not as spectacular as deleting an entire architecture, but it's still a worthy reduction in lines of code. Untested due to lack of hardware and not understanding how to set up a target platform. Changes from v1: - Fixed bugs pointed out by Jens in iscsit_wait_for_tag() - Abstracted out tag freeing as requested by Bart

Removing the percpu_ida code nets over 400 lines of removal. It's not as spectacular as deleting an entire architecture, but it's still a worthy reduction in lines of code. Untested due to lack of hardware and not understanding how to set up a target platform. Changes from v1: - Fixed bugs pointed out by Jens in iscsit_wait_for_tag() - Abstracted out tag freeing as requested by Bart

From: Matthew Wilcox <mawilcox at microsoft.com> This is a pretty rough-and-ready conversion of the target drivers from using percpu_ida to sbitmap. It compiles; I don't have a target setup, so it's completely untested. I haven't tried to do anything particularly clever here, so it's possible that, for example, the wait queue in iscsi_target_util could be more clever, like