hierarchicalforecast
Hierarchical Methods Time Series Forecasting
Hierarchical Methods Time Series Forecasting
To install this package, run one of the following:
HierarchicalForecast offers a collection of reconciliation methods,
including BottomUp, TopDown, MiddleOut, MinTrace and ERM.
Classic reconciliation methods:
BottomUp: Simple addition to the upper levels.TopDown: Distributes the top levels forecasts trough the hierarchies.Alternative reconciliation methods:
MiddleOut: It anchors the base predictions in a middle level. The levels
above the base predictions use the bottom-up approach, while the levels below
use a top-down.MinTrace: Minimizes the total forecast variance of the space of coherent
forecasts, with the Minimum Trace reconciliation.ERM: Optimizes the reconciliation matrix minimizing an L1 regularized objective.Summary
Hierarchical Methods Time Series Forecasting
Last Updated
Jan 22, 2026 at 15:06
License
Apache-2.0
Total Downloads
20.3K
Version Downloads
82
Supported Platforms
GitHub Repository
https://github.com/Nixtla/hierarchicalforecastDocumentation
https://nixtla.github.io/hierarchicalforecast/