Hi, I want using zero-inflated negative binomial regression model to classify data(a vector of data), that is I want know each observed value is more likely belong to the "zero" or "count" distribution(better with relative probability). My data is some like:
count site samp 12909 1 1 602 1 2 50 1 3 1218 1 4 91291 1 5 while "count" is the data with a mixture of "zero" and "non-zero" distribution I want know, and "site", "samp" are two prediction valuables with additive effect(but I am not interested in it). I have tried the zeroinï¬ function of pscl package to fit zero-inflated negative binomial regression. But it can not give you the classification result of "count". Can anyone help with some indication of how to do it or other tools that can do this job ?? -- Kai Ying Iowa State University ISU, Ames IA 50010 Email: yi...@iastate.edu [[alternative HTML version deleted]]
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