Dear all, I am running a catch rate estandardization of fishery dependent data using a ZINB model with an offset like this:
>globalM<-zeroinfl(Ntot~offset(log(Effort))+ year+zone+year:zone+day | Depth, > dist="negbin",link="logit",data=DAT) I am exploring model averaging methods with the MuMIn library (MuMIn_1.13.4 in R version 3.1.2). To date I was able to obtain model averaging estimates of model parameters doing the following: >sfM1 <- dredge(globalM,fixed="count_offset(log(Effort))") >avgmod.95p <- model.avg(sfM1, cumsum(weight) <= .95) >confint(avgmod.95p) >avgm <- model.avg(sfM1, cumsum(weight) <= .95) But I am getting problems with predict function. Until I understood the function predict(object,..) needs the "modelList" attribute stored in the "model.selection" object and this should be done with the function get.models(). But, this is the error message that I have got when : >confset.95p <- get.models(sfM1, cumsum(weight) <= .95,fit=TRUE) Error in eval(expr, envir, enclos) : argument "offset" is missing, with no default Any help with this? I would really appreciate it. Many thanks, -- *Alexandre Alonso Fernández, PhD* Institute of Marine Research, IIM-CSIC Departamentof Marine Ecology and Resources Fisheries Ecology unit <https://twitter.com/FisheriesIIM> [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology