FoCo2: Coherent Forecast Combination for Linearly Constrained Multiple Time Series

   Authors

Daniele Girolimetto, Tommaso Di Fonzo

   Published

June 7, 2025

   Publication details

CRAN

   Links
Abstract

Methods and tools designed to improve the forecast accuracy for a linearly constrained multiple time series, while fulfilling the linear/aggregation relationships linking the components (Girolimetto and Di Fonzo, 2024)1. FoCo2 offers multi-task forecast combination and reconciliation approaches leveraging input from multiple forecasting models or experts and ensuring that the resulting forecasts satisfy specified linear constraints. In addition, linear inequality constraints (e.g., non-negativity of the forecasts) can be imposed, if needed.

  • 1 Girolimetto, D., and Di Fonzo, T. (2024). Coherent forecast combination for linearly constrained multiple time series. Working paper. arXiv:2412.03429

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