Hello everyone- I have several sets of data that I fit (using MLE) to several uncommon distributions (betabinomial, zero-inflated negative binomial, zero-inflated betabinomial, zero-inflated binomial etc...).
I used dzinbinom from the emdbook package, corresponding to Benjamin Bolker's book, Ecological Models and Data in R, and dzibinom and dzibb as developed on page 285-286 of this book. I have compared them using AIC values (with AICtab from the bbmle package), but I would still like to do a goodness of fit test on the "winner" to see if it is a reasonable distribution. goodfit() from vcd can only take poisson, binomial, and nbinomial. I would like to use chisq.test, but I am having trouble coming up with the reference distribution. I followed an example on page 287 of this book where the reference distribution is calculated using dzibb, and then used it in the slot for p, a vector of probabilities: ZIBBprob=dzibb(1:size, prob=blurf1, theta=blurf2, size=blurf3, zprob=blurf4) chisq.test(tabulate(obs),p=ZIBBprob) My problem is that the ZIBBprob vector does not add up to 1... Is this because I am mis-using dzibb? Does anyone have any suggestions on how I can perform GOF tests on these weirdo distributions? Thanks Erika Mudrak ------------------------------------------- Erika Mudrak Graduate Student Department of Botany University of Wisconsin-Madison 430 Lincoln Dr Madison WI, 53706 608-265-2191 mud...@wisc.edu _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
