similar to: Multivariate dispersion & distances

Hello! After performing an analysis with betadisper, package vegan I would like to plot the results - so far, so good. But I would also like to "tune" a little bit the plotting characters, as '+' and 'x' are a little to similar... My (boiled down) code: [See session info at the bottom of the mail, vegan is vegan_2.0-3] mod <- betadisper(mydata, mygroups,

Hello, I tried to make a betadisper plot; however, it is quite messy at the moment with lines and symbols. I made two plots, one focusing on sites and the other on treatments. This is the code that I used: plot(betadisper(vegdist(y.nth,method="euclidean"),site)) plot(betadisper(vegdist(y.nth,method="euclidean"),treatment)) I have a few questions pertaining to how I could

Hallo List, I'm trying to implemement a restricted permutation scheme in permutest(). More precisely I have dependence in my data that should be allowed for in the permutation - I simulated the problem in the example of the vegan documentation p.24: library(vegan) data(varespec) ## Bray-Curtis distances between samples dis <- vegdist(varespec) ## First 16 sites grazed, remaining 8 sites

Hi, Thanks to all in advance, In recent I need policy based routing on my Linux2.4.3 box. requirement is like to give access of Internet to some computers while this facility is not available to rest people (That is based on MAC address only). My existin routing in "table main" is... 192.168.1.0/26 dev eth0 proto kernel scope link src 192.168.1.3 192.168.1.64/26 dev eth1 proto

Hi All, I have a question which does not pertain directly to the use of R but comes from my use of R! I have data which can be described as 3-dimensional e.g. (x,y,z), with no negative component. The suggested way to analyze this data is via multivariate techniques or by calculating what amounts to a levene's test on the data and then an ANOVA on the three components if the first test is

Dear vegan team, Vegan development happens now completely in github. R-Forge repository is no more in sync with github. I tried to commit all github changes to R-Forge, but a week ago I got a conflict in file and I haven't had time to resolve that conflict. You can follow vegan development and vegan discussion also without signing to github. The system seems to be completely open and does not

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

Dear WizaRds, although this might be a trivial question to the community, I was unable to find anything solving my problem in the help files on CRAN. Please help. Suppose I have 4 variables and want to use all possible combinations: 1,2 1,3 1,4 2,3 2,4 3,4 for a further kmeans partitioning. I tried permutations() of package e1071, but this is not what I need. Thank you for your help and

Dear R developers, I was looking for a function analogous to base::diag() for getting and setting bands of a matrix. The closest I could find was Matrix::band(), but this was not exactly what I wanted for two reasons. Firstly, Matrix::band() returns a matrix rather than just the specified band. Secondly, Matrix::band() cannot be used for setting the values for a matrix band. Setting or

*Dear R-help: My name is Rodrigo and I have a question with nlme package in R to fit a mixed beta regression model. The details of the model are: Suppose that:* *j in {1, ..., J}* *(level 1)* *i in {1, ..., n_j}* *(level 2)* *y_{ij} ~ Beta(mu_{ij} * phi_{ij}; (1 - mu_{ij}) * phi_{ij}) y_{ij} = mu_{ij} + w_{ij} * *with* *logit(mu_{ij}) = Beta_{0i} + Beta_{1i} * x1_{ij} + b2 * x2_{ij}

*Dear R-help: My name is Rodrigo and I have a question with nlme package in R to fit a mixed beta regression model. I'm so sorry. In the last email, I forgot to say that W is also a unknown parameter in the mixed beta regression model. In any case, here I send you the correct formulation. ** Suppose that:* *j in {1, ..., J}* *(level 1)* *i in {1, ..., n_j}* *(level 2)* *y_{ij} ~

Hello, Can someone point me to documentation or ideas on how to calculate the centroids of clusters identified with hclust ? I would like to be able to chose the number of clusters (in the style of cutree) and then get the centroids of these clusters. This seems like a quite obvious task to me, but I haven't been able to put my hands on a relevant command. Thank you, Moritz

Dear all, As our previous email did not get any response, we try again with a reformulated question! We are trying to do something which needs an efficient loop over a huge array, possibly functions such as apply and related (tapply, lapply...?), but can't really understand syntax and examples in practice...i.e. cant' make it work. to be more specific: we are trying to apply a mask

Dear r-help members, Could any of you help me with this model, please? This model gives error when some value touch whatever border and I do not know how to correct it. The 80% of the seeds produced by a plant will fell into the parent cell, the 15% in the first ring according to the king movement (in chess), and a 5% in the second ring defined by the queen2 matrix. Someone said me the functions

I am out of my league with this question. The following code starts the java imaging program ImageJ from within R, and displays an image (assuming ImageJ is installed on your computer). library(RImageJ) img <- IJ$openImage( file.choose() ) #pick an available .tif file img$show() # make the image object visible # An image is now displayed # find out about the objects involved >

I need to refresh my memory on Probability Theory, especially on conditional probability. In particular, I want to solve the following two problems. Can somebody point me some good books on Probability Theory? Thank you! 1. Z=X+Y, where X and Y are independent random variables and their distributions are known. Now, I want to compute E(X | Z = z). 2.Suppose that I have $I \times J$ random number

I found a bug in one of the fourteen speed patches I posted, namely in patch-vec-subset. I've fixed this (I now see one does need to duplicate index vectors sometimes, though one can avoid it most of the time). I also split this patch in two, since it really has two different and independent parts. The patch-vec-subset patch now has only some straightforward (locally-checkable) speedups for

Dear list, I posted essentially this same question to the r-sig-geo mailing list last week with no response :( Unfortunately I am no closer to reaching a solution, so I now post it here (with some clarifications) in the hope that someone following this list might have an answer for me: Has anyone had much experience with spatial interaction (or gravity) models, specifically in the form of

Dear R-users Coming from a proc mixed (SAS) background I am trying to get into the use of (n)lme. In this connection, I have some (presumably stupid) questions which I am sure someone out there can answer: 1) With proc mixed it is easy to get a hold on the estimated variance parameters as they can be put out into a SAS data set. How do I do the same with lme-objects? For example, I can see the

Hi, I am trying to parameterize the following mixed model (following Piepho and Ogutu 2002), to test for a trend over time, using multiple sites: y[ij]=mu+b[j]+a[i]+w[j]*(beta +t[i])+c[ij] where: y[ij]= a response variable at site i and year j mu = fixed intercept Beta=fixed slope w[j]=constant representing the jth year (covariate) b[j]=random effect of jth year, iid N(0,sigma2[b]) a[i]=random