Coherent Forecast Combination for Linearly Constrained Multiple Time Series
Cross-sectional covariance matrix approximation
Cross-sectional optimal multi-task forecast combination
Cross-sectional optimal coherent forecast combination
Cross-sectional sequential combination-reconciliation
Cross-sectional sequential reconciliation-combination
FoCo2: Coherent Forecast Combination for Linearly Constrained Multiple...
Matrices for the optimal coherent forecast combination
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 <doi:10.48550/arXiv.2412.03429>). '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.
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