I'm trying to fit a hurdle/zero-inflated (I haven't decided yet) model on microbiological water quality data that is also right-censored: either the water sample is contaminated with bacteria or not, and if contaminated, the number of colonies can go from 1 to 99 and "more than 100" (because it was not possible to count the number of colonies beyond 100 - often referred in microbiology as "TNTC = too numerous to count").
If I refer to the data example taken by Kleiber and Zeileis (https://www.statistik.uni-dortmund.de/useR-2008/slides/Kleiber+Zeileis.pdf) I'm in a situation where the "number of visits to the physician" is censored to let's say "30 visits or more".
Is there a way to combine a hurdle or zero-inflated model (from the package pscl for example) with this right censored data distribution ? A sort or combined hurdle / ZIP + tobit model ??
Thanks a lot for your help Lily