I am building a prediction model that tries to predict 'sales'. My dataset contains sales(quantity) and around 60 features. The features are mostly weather features (e.g. temperature, humidity, sunshine hour duration) and binary weekday(info) (monday 0 or 1, tuesday 0 or 1, holiday 0 or 1).
I built my Generalized Linear Model but I am not sure what 'family' and 'link' to chose.
Currently it looks like this
model_1 <- glm(quantity ~., data = train_set)
My dependent variable (sales) is distributed as follows:
Hope someone can inform me about which family and link to chose.