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I'm attempting to run 250 permutations of a negative binomial GLM model for data on fish counts. Many of the models are fit appropriately, but some issue warnings such as "convergence not reached" or "step size truncated due to divergence." I've attempted using glm.nb from the MASS package and the negbin function from the AOD package, but both still cause some models to

I have tried glm.nb in the MASS package, but many models (I have 250 models with different combinations of predictors for fish counts data) either fail to converge or even diverge. I'm attempting to use the negbin function in the AOD package, but am unsure what to use for the "random" term, which is supposed to provide a right hand formula for the overdispersion parameter.

This is my first time running GAMs in R. My csv file has these column headings: "X" "Y" "Sound" "Atlantic" "Blacktip" "Bonnet" "Bull" "Finetooth" "Lemon" "Scalloped" "Sandbar" "Spinner" "Abundance" "Diversity"

Hi, Is there a way, preferably with R, to read shapefiles and transform them in a format that I could then use with package PBSmapping? I have been able to read such files into R with maptools' read.shape and plot it with plot.Map, but I'd like to bring the data to PBSmapping and plot from there. I also looked at the package shapefile, but it does not seem to do what I want

Hello everyone (and Hadley in particular), I often need to plot data from multiple datasets on the same graph. A common example is when mapping some values: I want to plot the underlying map and then add the points. I currently do it with base graphics, by recording the maximum region in which my map+point will fit, plotting both with these xlim and ylim parameters, adding par (new=T)

Hi, I appologise if this is a rudimentary question and long winded but I just wanted to let ye know where I'm comming from. I'm new to R and I'm trying to use the 'randomForest' package to classify and predict. The Error message that is troubling me is: > pr<-predict(predictors,rf1, ext=ext) Error in x[...] <- m : NAs are not allowed in subscripted assignments In