similar to: R and marine protected areas: algorithms for site selection

Dear listers, I need to export a distance matrix in the following format : a 0.0 1.0 0.2 1.0 1.0 b 1.0 0.0 1.0 1.0 1.0 c 0.2 1.0 0.0 1.0 1.0 d 1.0 1.0 1.0 0.0 1.0 e 1.0 1.0 1.0 1.0 0.0 I tried write.matrix() from the MASS library, which gives: a b c d e 0.0 1.0 0.2 1.0 1.0 1.0 0.0 1.0 1.0 1.0 0.2 1.0 0.0 1.0 1.0 1.0 1.0 1.0 0.0 1.0 1.0 1.0 1.0 1.0 0.0 Does anyone know of an R trick to change

Dear Listers, I am trying to match tables that DO NOT have the same length. The tables result from the function "table()" so they look like this: table 1 2 3 4 3 5 7 table 2 1 2 3 6 4 5 I need the following output: (NOTICE THE ZEROS) 1 2 3 4 table1 0 3 5 7 table2 6 4 5 0 Unfortunately, I was not successful using "match()". Previous postings explain how to do

Dear Listers, I emailed the list a few days ago about how to bootstrap a community matrix (species by sites) and get a consensus tree with node support. A friend pointed out that a similar question remained unanswered in 2004. I wish to re-word my question: is anyone aware of a package / method to obtain a majority-rule consensus tree from x distance matrices ? Is anyone using R to generate

Hello all, R just ''stopped working'' on my machine (ibook g4, os 10.3.9). between last time I used it and now, I did not do anything but check emails and browse the internet. when I try to start the GUI, it appears and disappears as rapidly. when I tried to run a session from the terminal, I got the following: mkdir: /tmp/Rtmp590-29493: Permission denied mkdir:

Dear listers, I am trying to assess variance components for a nested, mixed-effects model. I think I got an answer that make sense from R, but I have a warning message and I wanted to check that what I am looking at is actually what I need: my data are organized as transects within stations, stations within habitats, habitats within lagoons. lagoons: random, habitats: fixed the question is:

I have a piece of code (from Xie et al. 2009 Autophagy 5:217) that runs in R and requires the glpk package. A year or so ago, I was able to download and install the glpk package directly from insider the R program (for Windows), and everything worked fine. Now I have installed R for Windows on a new computer, and I cannot find the glpk package on the list of available packages on my local

Recently, a package for convex optimization was announced for Python, based upon the LP solver GLPK, the SDP solver in DSDP5, and the LP and QP solvers in MOSEK. I'm aware GLPK is available for R, but wondered if anyone had good packages for convex optimization along these lines for R. TIA.

Hi. I am aware of three different R packages for linear programming: glpk, linprog, lpSolve. From what I can tell, if there are N variables and M constraints, all these solvers require the full NxM constraint matrix. Some linear solvers I know of (not in R) have a sparse matrix input format. Are there any linear solvers in R that have a sparse matrix input format? (including the

The R interface to the GNU Linear Programming Kit (GLPK) is now available on CRAN. The R interface functions are almost identical to the native GLPK C API making it easy to move code and concepts between R and C. The GLPK package is intended for solving large-scale linear programming (LP), mixed integer linear programming (MIP), and other related problems. The GLPK library includes the

The R interface to the GNU Linear Programming Kit (GLPK) is now available on CRAN. The R interface functions are almost identical to the native GLPK C API making it easy to move code and concepts between R and C. The GLPK package is intended for solving large-scale linear programming (LP), mixed integer linear programming (MIP), and other related problems. The GLPK library includes the

In my post at https://stat.ethz.ch/pipermail/r-help/2011-October/292019.html I included an undefined term "ej". The problem code should be as follows. It seems like a simple linear programming problem, but for some reason my code is not finding the solution. obj <- c(rep(0,3),1) col1 <-c(1,0,0,1,0,0,1,-2.330078923,0) col2 <-c(0,1,0,0,1,0,1,-2.057855981,0) col3

Can optimisation (simplex etc) be done through R?

Does anyone know whether R has its own modeling language for optimization problems (like SIMPLE in NuOPT for S-plus)? Paolo

Hello, My name is Sivan and I am a master degree student in statistics,my problem is as follows: I have a dataset containing gene sequences and I would like to create a phylogenetic tree from it. The problem that I can't seem to find a function to do this kind of operation. I read the ape package manual and I haven't found a command that takes raw data and turns it into a tree. does anyone

Dear everyone, I don't know much about Integer Programming but am afraid I am facing a problem that can only be solved via Integer Programming. I was wondering if those of you who have experience with it could recommend an R package. I found the following R packages: Rglpk glpk lpSolve lpSolveAPI Are there any others? Are some of them easier to use than others for a beginner? Any advice

On 08/04/2011 11:35, FlyLanguage wrote: > Do your own benchmarking, on the stuff that matters to you. It's the > only fair benchmark you'll ever see. I agree, but this is somewhat extreme point of view. Some general comparisons could also be of interest. For example, performance comparison of some deterministic software like GLPK solver, or compiler itself would be interesting to

Hello everybody, I am looking for a function (or package) which can solve a integer optimization problem. I have found the glpk package but I don't known very well how to use it. Someone has another solution ? thx

Hello R-help, Does anyone know if the sliding-box lacunarity analysis of Allain & Cloitre [1] / Plotnick et al. [2] has been implemented by anyone in R? I've come up blank on searches of help files, mailing lists and from googling r-project.org. Thanks in advance, Rich [1] C. Allain and M. Cloitre, 1991. Phys. Rev. A 44, p. 3552. [2] RE Plotnick, RH Gardner, WW Hargrove, K

Hi - A little while ago I posted a question about the implementation of a two-dimensional analog of the Kolmogorov-Smirnov test in R[1][2]. As there isn't one, as far as I know, people might be interested in a very fast C++ implementation called MUAC which is available as a function and as a standalone program from http://www.acooke.org/jara/muac/index.html. Apparently the code is

dear R users, I have troubles performing Moran.I test as suggested on http://www.ats.ucla.edu/stat/r/faq/morans_i.htm my spatial data are longitude and lattitide of communities. The calculation of the inverse distance matrix according to the homepage (using my data) datAL <- read.csv2("C:\\Konvergenz AL.csv", header=T) ALdist <- as.matrix(dist(cbind(datAL$L?nge,