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hey @Kyle Schmaus! That would be awesome! If I understand correctly, ARFIMA models are local (one model per time series). If that’s correct, maybe we could include them in the

statsforecast

library, because

mlforecast

is designed to train machine learning models globally (one model for all the time series). We would be delighted if you could collaborate on this new feature by sending us a PR. Let me know what you think! We can also guide you on how to collaborate on our repos. 🙂

@fede (nixtla) (they/them) Thank you for being open to the idea 💡 ! I think one could do ARFIMA in

statsforecast

, but I was more interested in enabling non-integer differencing in

mlforecast

. So right now I think if I wanted to difference hourly data once I might use

differences=[24]

(I might pick another interger too ) or if I wanted to difference twice I might do

differences=[24, 24]

. There are some use cases where I want to the difference order to be a number between 1 and 2.

Oh, that makes total sense for the

mlforecast

library. Let’s use github issues to communicate more visibility for users about the new feature. Feel free to ping me on Github so I can help you with whatever you need. Thank you, Kyle! This is exciting :)

Sounds great - I'll try to drop something by early next week (spinning plates till then)