I'm modeling claim count using glm. My data contains both continuous and categorical data. Data is aggregated to 6000 risk profiles(referenced here by ID). Exposure for a policyholder for 1 year
In fact, As far as I know, I must probably convert my continuous variables to categorical, is that all I have to do? I'll be modeling my glm using first Poisson and N.B type 2, I also think I might use exposure as an offset? Also, should ID and Year, stay as an explanatory variable?