The FoReco (Forecast Reconciliation) 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.

It offers 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 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.

You can install the stable version on R CRAN

install.packages("FoReco")

You can also install the development version from Github

# install.packages("devtools")
devtools::install_github("daniGiro/FoReco")

• Source code: https://github.com/daniGiro/FoReco
• Site documentation: https://danigiro.github.io/FoReco/

If you encounter a clear bug, please file a minimal reproducible example on GitHub.