How does the hierarchicalforecast package (+ statsforecast) handle multiple TS that don't have the same dates? I notice that

aggregate

adds leading, but do those zeros affect the statsforecast models? For instance if one TS started in January 2019 and other started in April 2019, the 2nd TS would have zeros added after using

aggregate

, but do those zeros affect model performance?

hey @Isaac! If I understand correctly, after applying

aggregate

the 2nd ts has zero values from January 2019 to April 2019? I think this is an unexpected behavior; those zeros will probably negatively impact the model’s performance. Could you help us open an issue on the github repo to investigate the problem? Here’s the link: https://github.com/Nixtla/hierarchicalforecast/issues/new Thank you!

Yes. And if you try and remove the zero's, you're unable to reconcile, because there's a shape issue with the fitted dataset

thank you @Isaac! We’ve opened a PR fixing the issue (https://github.com/Nixtla/hierarchicalforecast/pull/190). We will merge it into the main branch and publish a new version soon. In the meantime, you can test the changes installing from that branch:

pip install git+<https://github.com/nixtla/hierarchicalforecast.git@189-aggregate-adds-leading-zeros-to-series-with-different-dates>

. Please let us know if this helps or if something else needs to be clarified. :)

Cool cool, I'll take a look. Did you test whether

reconcile

still works as expected?

Hey @Isaac! Thanks for letting us know about the problem, we’ll be working on it 🙂

Good to know. Let me know if I can help 🙂

hey @Isaac! We’ve pushed the fixes into the main branch. We will release a new version in the following days :)

Woohoo! Excited to try it out. I also saw the conformal predictions in statsforecast coming out soon 👀

Nice! Feel free to let us know if something breaks or if you need any help. Yeah! We are excited about conformal prediction in stats, we have to finish some details, but in the next weeks should be released 🎉

Any update on when the new hierarchicalforecast package will be released?