similar to: Null models of species co-occurrence

Hi R Helpers, I'm still new to R and i experience many difficulties..I'm using vegan package (R version 2.11) trying to calculate checkerboard units for each species pair of a matrix. I've prepared the function: pair.checker=function (dataset) {designdist (dataset, method="c("(A-J)x(B-J)", terms ="binary", abcd=FALSE)} to use with function oecosimu as

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Here's a question for ecologists on the r-help list-- I'm addressing this to ecologists in particular because they're most likely to be familiar with the equation in question but I'll be happy to discuss the problem with anyone who's willing to take a whack at it. I'm trying to write a function to calculate the large sample variance of species richness estimates by

Dear list, I have 603 numbers depicting range sizes of birds in Japan. I would like to learn if the 603 range sizes are randomly distributed or not, in order to check if they meet mid-domain effects. Please kindly advise if any R package or function can check the fit. Also, any more references are highly appreciated. Thank you Elaine [[alternative HTML version deleted]]

Hi all, I hope that i've posted this in the correct place. if not, please accept my apologies (where should this go?) I have carried out experimental removal of bivalves at 2 intertidal shores. Bivalves were removed by raking of surface sediments. I wish compare the biomass values of for a total of 8 species between the 2 shores My 3 treatments are: Undisturbed Controls (Cont), Procedural

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! I wish to know if there is any R forum which is meant only for Statistics? I mean where we can clarify our statistics doubts and seek knowledge. I know there are lot many books and internet sites, but 'R forum' has altogether different standard and very high level and one can learn a lot from them. Regards Vincy [[alternative HTML version deleted]]

It is not about "really arge total number of observations", but: set.seed(4711);tabs <- r2dtable(1e6, c(2, 2), c(2, 2)); A11 <- vapply(tabs, function(x) x[1, 1], numeric(1));table(A11) A11 0 1 2 166483 666853 166664 There are three possible matrices, and these come out in proportions 1:4:1, the one with all cells filled with ones being most common. Cheers, Jari

Hello, While doing some enrichment tests using chisq.test() with simulated p-values, I noticed some strange behaviour. The computed p-value was extremely small, so I decided to dig a little deeper and debug chisq.test(). I noticed then that the simulated statistics returned by the following call tmp <- .Call(C_chisq_sim, sr, sc, B, E) were all the same, very small numbers. This, at first,

> On 25 Aug 2017, at 11:23 , Jari Oksanen <jari.oksanen at oulu.fi> wrote: > > It is not about "really arge total number of observations", but: > > set.seed(4711);tabs <- r2dtable(1e6, c(2, 2), c(2, 2)); A11 <- vapply(tabs, function(x) x[1, 1], numeric(1));table(A11) > > A11 > 0 1 2 > 166483 666853 166664 > > There are

>>>>> Gustavo Fernandez Bayon <gbayon at gmail.com> >>>>> on Thu, 24 Aug 2017 16:42:36 +0200 writes: > Hello, > While doing some enrichment tests using chisq.test() with simulated > p-values, I noticed some strange behaviour. The computed p-value was > extremely small, so I decided to dig a little deeper and debug >

> On 25 Aug 2017, at 10:30 , Martin Maechler <maechler at stat.math.ethz.ch> wrote: > [...] > https://stackoverflow.com/questions/37309276/r-r2dtable-contingency-tables-are-too-concentrated > > >> set.seed(1); system.time(tabs <- r2dtable(1e6, c(100, 100), c(100, 100))); A11 <- vapply(tabs, function(x) x[1, 1], numeric(1)) > user system elapsed >

>>>>> "MM" == Martin Maechler <maechler@stat.math.ethz.ch> >>>>> on Thu, 11 Dec 2003 18:29:05 +0100 (CET) writes: >>>>> "Torsten" == Torsten Hothorn <torsten@hothorn.de> >>>>> on Thu, 11 Dec 2003 18:03:07 +0100 (CET) writes: Torsten> On Thu, 11 Dec 2003, Jeffrey Chang wrote:

Dear R-users, I set up an experiment where I put up bluebird boxes across an urbanization gradient. I monitored these boxes and at some point I pulled a feather from a chick and a friend used spectral properties (rtot, a continuous var) to index chick health. There is an effect of sex that I would like to include but how would I set up a regression and look at the effect of urbanization

Hi I am new to Cygwin and Linux. I installed R under Cygwin as part of the setup I chose "All" during installation, for all packages. So I have the FULL installlation of cygwin up and running, including gfortran. *Under Cygwin, how do I check and configure the path to the various libraries?* I am trying below command and it says, cannot find "lgfortran" But I have installed

Dear All, I have a problem understanding the difference between the outcome of a fisher exact test and a chi-square test (with simulated p.value). For some sample data (see below), fisher reports p=.02337. The normal chi-square test complains about "approximation may be incorrect", because there is a column with cells with very small values. I therefore tried the chi-square with

Hello R-users, I would like to generate two-way contingency tables with zero in one cell. I tried to use the function r2dtable but I could not force one cell to have zero value. Any Idea? Best regards.. Mahmoud [[alternative HTML version deleted]]

Dear List members, I would like to test whether an observed occupancy of lakes in a landscape has occurred randomly (by chance) or not. How can I do that? The problem is that it concerns only a single species and I would like to use binary data only. At first I thought of generating null models and test the observed occupancy against the randomly generated one. However, this needs more than one

Hi everyone, I am working with the dbFD function of the FD package, and there's something funny happening with the value of sing.sp in the output. Basically, I have a species-function matrix and a community matrix. One site in particular has 6 species, 4 of which have identical functional coding. I thus expect nbsp = 6 and sing.sp = 2 for this site. However, nbsp = sing.sp = 6. This

Dear all, I am new to R and even newer to mapping with R. I have installed PBSMapping, maptools and maps, and I am struggling to produce a map of fish abundance in the Grand Banks. I have tried several approaches to plot the bathymetry in my study area: 1) download the data from http://topex.ucsd.edu/cgi-bin/get_data.cgi (42N46N313W307W) To start with, the map I get is blank between