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Forecast Reconciliation is a a post-forecasting process aimed to improve the accuracy and align forecasts for a system of linearly constrained (e.g. hierarchical/grouped) time series. The FoReco package provides a comprehensive set of classical (bottom-up, top-down and middle-out), and modern (optimal and heuristic combination) forecast reconciliation procedures in different frameworks including cross-sectional, temporal, or cross-temporal settings.

The core functions for reconciliation categorized by framework are as follows:

Reconciliation Cross-sectional Temporal Cross-Temporal
Classical reconciliation
Top-down: *td() cstd() tetd() cttd()
Bottom-up: *bu() csbu() tebu() ctbu()
Middle-out: *mo() csmo() temo() ctmo()
Regression‑based reconciliation
Least squares: *rec() csrec() terec() ctrec()
LCC: *lcc() cslcc() telcc() ctlcc()

Additionally, FoReco provides various functions for different aspects of forecast reconciliation, including aggregating time series, balancing hierarchies, computing projection and covariance matrices, and more.


You can install the stable version on R CRAN

You can also install the development version from Github

# install.packages("devtools")

Getting Started

To get started with using the FoReco package, refer to the documentation for detailed information on how to apply different forecast reconciliation procedures to your data.

Issues and Contributions

If you encounter any bugs or have suggestions for improvements, please feel free to report them on GitHub Issues page. Contributions are also welcome!