An R package offering classical (bottom-up and top-down), and modern (optimal and heuristic combination) forecast reconciliation procedures for cross-sectional, temporal, and cross-temporal linearly constrained time series.
The FoReco package is designed for forecast reconciliation, a
post-forecasting process aimed to improve the accuracy of the base
forecasts for a system of linearly constrained (e.g. hierarchical/grouped) time series.
The main functions are:
htsrec():cross-sectional (contemporaneous) forecast reconciliation.
thfrec():forecast reconciliation for a single time series through temporal hierarchies.
lccrec():level conditional forecast reconciliation for genuine hierarchical/grouped time series.
tdrec():top-down (cross-sectional, temporal, cross-temporal) forecast reconciliation for genuine hierarchical/grouped time series.
ctbu():bottom-up cross-temporal forecast reconciliation.
tcsrec():heuristic first-temporal-then-cross-sectional cross-temporal forecast reconciliation.
cstrec():heuristic first-cross-sectional-then-temporal cross-temporal forecast reconciliation.
iterec():heuristic iterative cross-temporal forecast reconciliation.
octrec():optimal combination cross-temporal forecast reconciliation.
Di Fonzo, T., and Girolimetto, D. (2023), Cross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives, International Journal of Forecasting, 39(1), 39-57 doi:10.1016/j.ijforecast.2021.08.004 .
Di Fonzo, T., Girolimetto, D. (2022), Forecast combination based forecast reconciliation: insights and extensions, International Journal of Forecasting, in press.
Girolimetto, D., Athanasopoulos, G., Di Fonzo, T., and Hyndman, R. J. (2023), Cross-temporal Probabilistic Forecast Reconciliation, doi:10.48550/arXiv.2303.17277 .
Useful links: