Thanks for the quick reply, I understand that the predict(zip1A, type = "response") command is computing the fitted_means and these are different than the probabilities predict(zip1A, type = "prob"). Although, according to Martin (2005), the highest probabilities do not simply lead to the true count estimates: "to get the true estimate of relative mean abundance from the ZIP one must multiply the estimated relative mean number of individuals at a site by the probability that the relative mean number of individuals at a site is generated through a Poisson distribution."
I initially thought that the predicted mean and the observed count could be compared to estimate the fit of the model, but now I am not sure what to think with Martin (2005) statement. Thank you for your help, JM Martin, T.G. et al. (2005) Zero tolerance ecology: improving ecological inference by modelling the source of zero observations, Ecology Letters, Volume 8, Issue 11, pages 1235–1246. -- View this message in context: http://r.789695.n4.nabble.com/Zero-inflated-regression-models-predicting-no-0s-tp3564807p3568865.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
