Package: foresightr
Title: Forecasts Chosen by What Would Have Worked
Version: 0.1.1
Authors@R: c(
    person("André", "Leite", email = "leite@castlab.org", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-4718-9766")),
    person("Marcos", "Wasiliew", email = "marcos.wasiliew@gmail.com", role = "aut",
           comment = c(ORCID = "0009-0004-4694-3159")),
    person("Hugo", "Vasconcelos", email = "hugo.vasconcelos@ufpe.br", role = "aut",
           comment = c(ORCID = "0000-0001-6249-0920")),
    person("Carlos", "Amorim", email = "carlos.agaf@ufpe.br", role = "aut",
           comment = c(ORCID = "0000-0001-6315-8305")),
    person("Diogo", "Bezerra", email = "diogo.bezerra@ufpe.br", role = "aut",
           comment = c(ORCID = "0000-0002-1216-8674")),
    person("Júlia", "Nascimento Barreto", email = "juliabarreto@gd.seplag.pe.gov.br", role = "aut",
           comment = c(ORCID = "0009-0004-2851-7770")),
    person("The authors of the dependency Rust crates", role = "ctb",
           comment = "see inst/AUTHORS file for details"))
Description: 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.
License: MIT + file LICENSE
URL: https://github.com/StrategicProjects/foresightr,
        https://strategicprojects.github.io/foresightr/
BugReports: https://github.com/StrategicProjects/foresightr/issues
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
Depends: R (>= 4.2)
Imports: ggplot2 (>= 3.5.0), stats, tibble, utils
Suggests: testthat (>= 3.0.0), jsonlite, knitr, rmarkdown
Config/testthat/edition: 3
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.81
VignetteBuilder: knitr
Config/rextendr/version: 0.5.0
Config/roxygen2/version: 8.0.0
Config/pak/sysreqs: libclang-dev
Repository: https://strategicprojects.r-universe.dev
Date/Publication: 2026-09-30 18:04:18 UTC
RemoteUrl: https://github.com/strategicprojects/foresightr
RemoteRef: HEAD
RemoteSha: f4d94e4cdb0f001b4372cfecb207bfffb6d4f3b3
NeedsCompilation: yes
Packaged: 2026-10-14 14:08:27 UTC; root
Author: André Leite [aut, cre] (ORCID: <https://orcid.org/0000-0002-4718-9766>),
  Marcos Wasiliew [aut] (ORCID: <https://orcid.org/0009-0004-4694-3159>),
  Hugo Vasconcelos [aut] (ORCID: <https://orcid.org/0000-0001-6249-0920>),
  Carlos Amorim [aut] (ORCID: <https://orcid.org/0000-0001-6315-8305>),
  Diogo Bezerra [aut] (ORCID: <https://orcid.org/0000-0002-1216-8674>),
  Júlia Nascimento Barreto [aut] (ORCID:
    <https://orcid.org/0009-0004-2851-7770>),
  The authors of the dependency Rust crates [ctb] (see inst/AUTHORS file
    for details)
Maintainer: André Leite <leite@castlab.org>