Hierarchical Forecast

HierarchicalForecast, currently at version 1.5.1, is a Python library offering a comprehensive collection of cross-sectional and temporal reconciliation methods for hierarchical time series forecasting. It provides various reconciliation techniques, including BottomUp, TopDown, MiddleOut, MinTrace, and ERM, as well as probabilistic coherent prediction methods like Normality, Bootstrap, and Conformal. The library is actively maintained with regular releases and focuses on bridging the gap between statistical modeling and machine learning in time series analysis.