I'm attempting to model some data using regression analysis that has different upper limits for different observations, i.e. there is no universal limit for the entire data set. However I do have observations that have been censored, but the amount of censoring will sometimes change between observations? As I understand it the
censReg R package accepts one universal upper limit, is there another option either within this package or in another package/language that would allow me to model observations with different upper limits?
If there is no other option then would using a similar approach to zero-inflated models accurately model this behavior? And by that I mean build a model to estimate when an observation might be censored and include that in the final distribution of what I am trying to predict. That's the only approach I can think of that might help with this distribution behavior.