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Description

Forecast Reconciliation.

Classical (bottom-up and top-down), optimal and heuristic combination forecast point (Di Fonzo and Girolimetto, 2023) <doi:10.1016/j.ijforecast.2021.08.004> and probabilistic (Girolimetto et al. 2023) <arXiv:2303.17277> reconciliation procedures for cross-sectional, temporal, and cross-temporal linearly constrained time series.

FoReco logo

R-CMD-check CRANstatus Lifecycle:experimental develversion License:GPL-3

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.

Installation

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")

Links

Getting help

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

Metadata

Version

0.2.6

License

Unknown

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