Dear R community I'm new to R and I'd like to ask for hints how to approach the following problem: I have two vectors of count data 'observed_S' and 'observed_A'. Whereas 'observed_S' follows a neg. binomial distribution but 'observed_A' is a mixture of an unknown variable 'A' (also from a neg. binomial distribution) and a shadow of 'observed_S', so to say. Therefore my model can be expressed by: observed_A = factor*observed_S + A I d like to find the factor explaining my two data vector most coherently. but I m overwhelmed by the different packages dealing with neg. binomial distribution regression. Can someone please point me which package is most useful for the above described purpose? Thank you very much in advance Regards Fabian