The weights.jl file describes three types of weights: frequency weights, probability weights, and analytic weights.
This is an amazing feature to Julia, as only commercial software like STATA and SAS understand the differences between these 3 weights. R and Python only understand one type of weight, which I think is something like an importance weight.
Being able to use these 3 types of weights properly is crucial to the field that I work in (causal machine learning). Most software implementations use a single weight vector for everything - this will get you through weighted maximum likelihood but it will not be able to get you through proper causal inference (covariance matrix is dependent on what type of weight the user passed in). If Julia has a consistent use of fweights, pweights, and aweights it would be a very distinguishing factor. Are there any plans to standardize this for all functions throughout JuliaStats?