Over the summer, I worked on implementing a paper called How Big Should Your Data Really Be? Data-Driven Newsvendor: Learning One Sample at a Time. This paper derives a statical model which makes time series predictions on data with unbalanced costs and proves near-optimal theoretical guarantees on the performance of this model. I'm interested in possibly pushing my model to the statsforecast library. Would this be something @Max (Nixtla) or the team at Nixtla would be interested in?

Your paper looks really interesting, I will try to read it carefully. It looks also that you are beginning to look into reinforcement learning. :) We are also fans of quantile regression and its links to the News Vendor problem.

Hi @Eitan Turok, it would be an honor to have you as a contributor 🙂

Got it. I'm currently a student and am doing finals but after the semester ends, I will try to find some time to contribute.