similar to: Goodness-of-fit test for gamma distribution?

Hi I am experiencing a problem with the random number generator. When I call any function that involve RNG such as "runif" or "sample" I get this error: .Random.seed is not an integer vector but of type 'double' I can't coerce the random seed and it's recommended not to alter it anyway. Can anybody help me? Thanks and kind regards, Piero Visconti, PhD

Hi all, I am trying to model (continuous) spatial variation in a response variable as a function of one or more of several explanatory variables. I am principally interested in obtaining some measure of the relative "importance" of the explanatory variables. I have found several R libraries that are tailored to this sort of problem (geoR, geoRglm, gstat, etc.); however, as near

Hello List, My question is an elementary one. I have run a fuzzy kmeans cluster using FANNY to group freshwater fish assemblages. I then went in the field to validate that classification and have retrieved new assemblage data for a new suite of streams. Therefore I would like to use Predict to determine how well the original clustering fits the new data. However I have not figured out a

I'm trying out a basic plot, but something about the way I subset my data leads to problems with the plot. Here is the first bit of my data set year,date,location,quadrat_juvenile,photo_location,photo_exists,genus,count,divers 2005,2005-04-30, 1 Fringing Reef,1, 1 Fringing Reef Coral Transect Pole 1-2 Quadrat 1,t,Acanthastrea,0,HP+MEM 2005,2005-04-30, 1 Fringing Reef,1, 1 Fringing Reef

How can I print a data.frame to a PDF with pdf()...dev.off() ____________ Paulo E. Cardoso [[alternative HTML version deleted]]

For block effects with small variance, lmer will sometimes estimate the variance as being very close to zero and issue a warning. I don't have a problem with this -- I've explored things a bit with some simulations (see below) and conclude that this is probably inevitable when trying to incorporate random effects with not very much data (the means and medians of estimates are plausibly

Hello! I'm a PhD student working with coral reef fish diversity in Mexico. I want to do species accumulation curves but I have differential sampling effort for each "sample". Do you know or have developed an R script that consider the differential effort of each sample? PRIMER and other programs use each pack of species as a replica without the possibility of telling the program that

Have made a stacked area plot, but now want to manipulate the x axis: make in even increments (50) in order to suppress the tick marks (forming solid bar under plot). However, the plot functions do not seem to work, and I cannot find documentation for use of xat in stackpoly. This is a time series of data covering 579 years, and has been successfully converted from zoo to matrix. Data plotting

Dear all I have used the lda and predict functions to classify a set of objects of unknown origin. I would like to use a jackknife reclassification to assess the degree to which the outcomes deviate from that expected by chance. However, I can't find any function that allows me to do this. Any suggestions of how to generate the jackknife reclassification to assess classification accuracy?

Dear David, you asked this question a while ago on the R mailing list and got no answer. I have the same problem and was wondering if you had found a solution Cheers Loic Loic Thibaut, PhD candidate, ARC Centre of Excellence for Coral Reef Studies, School of Marine Biology, James Cook University, Townsville, Qld, 4811, Australia. Tel + 61 747 815 735, Fax: + 61 747 251 570, email:

> > just so you know, --enable-vorbis-updates is only a compile flag for the KH > > branch, not the mainline trunk. And I think it would be great to have this > > code be factored out of KH and integrated into the mainline trunk...This > > also seems like an odd thing to have as a compile flag, what was the > > motivation for that ? oddsock > That switch

Hi all, I am fairly new to R and I am trying to run mvpart and create a MRT using explanatory variables and covariables. I've been following the procedures in Numerical Ecoogy with R. The command (no covariables) which works fine - ABUNDTMRT <- mvpart(abundance ~ .,factors,margin=0.08,cp=0,xv="1se",xval=nrow(abundance),xvmult=100,which=4) where abundance is 4th root

Thanks Petr. Comments below: At 03:40 PM 18/05/2007, Petr Klasterecky wrote: >Sean Connolly napsal(a): >>Hi all, >>I am wondering if anyone has written (or knows of) a function that >>will conduct a goodness-of-fit test for a gamma distribution. I am >>especially interested in test statistics have some asymptotic >>parametric distribution that is independent

Hello, I recently started using the metafor package (version 1.6-0) in R (2.15.1, 64-bit Windows 7) and noticed that I was getting slightly different values when I manually calculated the standardized mean difference versus what escalc was giving me. Here''s a very simple example: escalc(measure="SMD", m1i=5,m2i=10,n1i=5,n2i=5,sd1i=1,sd2i=2,vtype="LS") The result

Hi there, I have been having trouble running negative binomial regression (glm.nb) using library MASS in R v2.15.0 on Mac OSX. I am running multiple models on the variables influencing the group size of damselfish in coral reefs (count data). For total group size and two of my species, glm.nb is working great to deal with overdispersion in my count data. For two of my species, I am getting a

Dear list, I have two dissimilarity matrices, one for a training data set which I then clustered using PAM. The second is a diss matrix for a validation data set (an independent field sample). I have been trying to use knn to distinguish distances between the validation data set and the 6 mediods of the training data defined by using PAM. I continue to get error messages in regards to either the

Dear all When plotting the results of lda and predict.lda, I expect the axis dimensions to remain essentially the same - predict.lda projects new observations onto linear discriminants. However, I am getting different ranges of values along the x-axis when producing plots following each: plot(lda) yields values in the range approximately -3 to +4, while plot(predict.lda) yields values for the

Dear All, I've been using mcmcsamp() successfully with a few different mixed models but I can't get it to work with the following. Is there an obvious reason why it shouldn't work with a model of this structure ? *brief summary of objective: I want to test the effect of no-fishing marine reserves on the abundance of a target species. I have samples at coral reef sites inside and

Here's the latest batch of words to get shipped out to Allison Smith. Please submit reasonably small changes to me by tomorrow 10:00 AM Eastern time, and I'll add them. As usual, donations to what will be a ~$110 USD expense would be appreciated, as I am paying for this round out of my pocket. Please send to paypal address "jtodd@loligo.com". I did not include all

RubyStuf.com, the premiere place for Ruby stuff, has some new, um, stuff. http://www.rubystuff.com/ Profoundly inspired by a series of ruby-talk threads on just how "dangerous" is Ruby comes "Ruby: You''ll shoot your eye out" shirts and mugs: http://www.cafepress.com/ruby_dangerous http://www.cafepress.com/rubyshootout (A big shout-out to David Koontz for the