Ola, 📣 We just released v1.1.0 of HierarchicalForecast, which adds the following features: • [FEAT] Add sparse non-negative OLS and WLS via QP for

MinTraceSparse

by @christophertitchen in #319 • [FEAT] Implement adjacency matrix by @christophertitchen in #332 • [FEAT] Extremely fast forecast proportions by @christophertitchen in #334 In addition, a number of bugs were fixed: • [FIX] Handle zero division in top down methods by @mattbuot in #325 • [FIX] Raise warning on NaN values when using average proportions and proportion averages methods by @janrth in #335 • [FIX] TopDown method failing on combinations with other methods by @elephaint in #330 • [FIX] ERM-reg and ERM-reg-bu equations by @elephaint in #331 • [FIX] Produce reproducable samples for PERMBU by @elephaint in #337 Thanks to @christophertitchen, @mattbuot and @janrth for their contributions! Questions or suggestions for new features? Let us know as a comment or file an issue on Github. Our next release will add temporal hierarchical reconciliation methods, which is in testing phase. Happy forecasting!

Cc @Khuyen Tran

@Max What should I do with this info? We could incorporate into the newsletter once we finish setting it up

@Khuyen Tran see also this post on the latest release of neuralforecast, I don't think we announced that one yet on social media: https://nixtla.slack.com/archives/C06HPUP0C7M/p1740758498228769