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conda-forge / packages / hierarchicalforecast 1.4.0

Hierarchical Methods Time Series Forecasting

copied from cf-post-staging / hierarchicalforecast

Installers

  • noarch v1.4.0

conda install

To install this package run one of the following:
conda install conda-forge::hierarchicalforecast

Description

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.

PyPI: https://pypi.org/project/hierarchicalforecast/


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