Dear all, I have a kind of a theoretical question from which I hope it might interest you and hopefully can help me a bit. In order to obtain ecological (surrvey) data, I try to make a prediction about the accuracy of a sampling tool to estimate mussel density. For this reason I took a lot of samples at a certain fixed location and counted the amount of mussels in each sample. Because mussels are aggregated on the sediment, I had a lot of zero values. To estimate the sample size I used a binomial distribution and obtained the k value and the mu from the fitdistr(x,"negative binomial") (MASS). The question I have is: how can I test if this distribution accurately described my (zero inflated count) data? I am a bit familiar with the AIC but since I only have counts on one variable I cannot perform a GLS. Creating a vector with rnbinom() using the k and mu from the fitdistr() I plotted a histogram and compared it with my data, this showed that is was roughly comparable, but I want to quantify this. I have a biological background not a statistical one, so I realize I can ask silly questions. But I hope someone can give me some hints. Kind regards, Jacob Capelle PhD student Wageningen Imares The Netherlands jacob.cape...@wur.nl <mailto:jacob.cape...@wur.nl>
_______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
