How to make mlogit more flexible

@mlogit covers most of the needs when you are running an multinomial logit model. It also offers great flexibility in model specification. However, sometimes you need more flexibility in your models. Here is how.

$\alpha=land$

mlogit I will use

But if you have a lot of missing values in your dataset, mlogit might not be the best options for the reasons in this answer