The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Time series forecasting that replays the past before trusting a model: a rolling-origin backtest, Tashman (2000) <doi:10.1016/S0169-2070(00)00065-0>, refits every candidate at each origin, the choice is made by out-of-sample error, and prediction intervals are quantiles of the errors actually observed, for each horizon and for totals of the next periods. Models include seasonal ARIMA by exact maximum likelihood with automatic orders, Hyndman and Khandakar (2008) <doi:10.18637/jss.v027.i03>; exponential smoothing in state space form, Hyndman, Koehler, Snyder and Grose (2002) <doi:10.1016/S0169-2070(01)00110-8>; the Theta method, Assimakopoulos and Nikolopoulos (2000) <doi:10.1016/S0169-2070(00)00066-2>; a trend with changepoints and events in the manner of Taylor and Letham (2018) <doi:10.1080/00031305.2017.1380080>; TBATS, De Livera, Hyndman and Snyder (2011) <doi:10.1198/jasa.2011.tm09771>; seasonal-trend decompositions by LOESS for one or several seasonal periods, Bandara, Hyndman and Bergmeir (2021) <doi:10.48550/arXiv.2107.13462>; the method of Croston (1972) <doi:10.1057/jors.1972.50> for intermittent demand; and ensembles. The computations are done by the 'Rust' crate 'foresight', bundled with the package.
| Version: | 0.1.1 |
| Depends: | R (≥ 4.2) |
| Imports: | ggplot2 (≥ 3.5.0), stats, tibble, utils |
| Suggests: | testthat (≥ 3.0.0), jsonlite, knitr, rmarkdown |
| Published: | 2026-10-13 |
| DOI: | 10.32614/CRAN.package.foresightr (may not be active yet) |
| Author: | André Leite foresightr author details |
| Maintainer: | André Leite <leite at castlab.org> |
| BugReports: | https://github.com/StrategicProjects/foresightr/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/StrategicProjects/foresightr, https://strategicprojects.github.io/foresightr/ |
| NeedsCompilation: | yes |
| SystemRequirements: | Cargo (Rust's package manager), rustc >= 1.81 |
| Materials: | README, NEWS |
| CRAN checks: | foresightr results |
| Reference manual: | foresightr.html , foresightr.pdf |
| Vignettes: |
The backtest and its intervals (source, R code) Decomposition and cleaning (source, R code) Get started (source, R code) The models (source, R code) Regressors and events (source, R code) |
| Package source: | foresightr_0.1.1.tar.gz |
| Windows binaries: | r-devel: not available, r-release: foresightr_0.1.1.zip, r-oldrel: foresightr_0.1.1.zip |
| macOS binaries: | r-release (arm64): foresightr_0.1.1.tgz, r-oldrel (arm64): foresightr_0.1.1.tgz, r-release (x86_64): foresightr_0.1.1.tgz, r-oldrel (x86_64): foresightr_0.1.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=foresightr to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.