I am currently running a double hurdle model with the R command "mhurdle". My data is not normally distributed and I am using the box cox normal distribution on because that yields the highest log likelyhood. The code I am using looks as follows: model <- mhurdle(var1 ~ age + income +var3 +habit +count | var5 +var6+var7 +var8 |0, data =d, dist ="bc", method ="bhhh") However, I am unsure if I have to backtransform the resulting model estimates of if I can interprete them as they are. If I need to backtransform, how would I do so?


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