<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Forecasting Functions for Time Series and Linear Models</dc:title>
  <dc:title>R package forecast version 9.0.2</dc:title>
  <dc:subject>CRAN Task View: Econometrics (https://CRAN.R-project.org/view=Econometrics)</dc:subject>
  <dc:subject>CRAN Task View: Environmetrics (https://CRAN.R-project.org/view=Environmetrics)</dc:subject>
  <dc:subject>CRAN Task View: Finance (https://CRAN.R-project.org/view=Finance)</dc:subject>
  <dc:subject>CRAN Task View: MissingData (https://CRAN.R-project.org/view=MissingData)</dc:subject>
  <dc:subject>CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries)</dc:subject>
  <dc:description>Methods and tools for displaying and analysing
             univariate time series forecasts including exponential smoothing
             via state space models and automatic ARIMA modelling.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.1.0)</dc:relation>
  <dc:relation>Imports: colorspace, fracdiff, generics (&gt;= 0.1.2), ggplot2 (&gt;= 3.4.0),
graphics, lmtest, magrittr, nnet, parallel, Rcpp (&gt;= 0.12.4),
stats, timeDate, urca, withr, zoo</dc:relation>
  <dc:relation>LinkingTo: Rcpp (&gt;= 0.12.4), RcppArmadillo (&gt;= 0.2.35)</dc:relation>
  <dc:relation>Suggests: forecTheta, knitr, methods, rmarkdown, rticles, scales,
seasonal, testthat (&gt;= 3.3.0), uroot</dc:relation>
  <dc:creator>Rob Hyndman &lt;Rob.Hyndman@monash.edu&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Rob Hyndman [aut, cre, cph] (ORCID:
    &lt;https://orcid.org/0000-0002-2140-5352&gt;),
  George Athanasopoulos [aut] (ORCID:
    &lt;https://orcid.org/0000-0002-5389-2802&gt;),
  Christoph Bergmeir [aut] (ORCID:
    &lt;https://orcid.org/0000-0002-3665-9021&gt;),
  Gabriel Caceres [aut] (ORCID: &lt;https://orcid.org/0000-0002-2947-2023&gt;),
  Leanne Chhay [aut],
  Kirill Kuroptev [aut],
  Maximilian Mücke [aut] (ORCID: &lt;https://orcid.org/0009-0000-9432-9795&gt;),
  Mitchell O'Hara-Wild [aut] (ORCID:
    &lt;https://orcid.org/0000-0001-6729-7695&gt;),
  Fotios Petropoulos [aut] (ORCID:
    &lt;https://orcid.org/0000-0003-3039-4955&gt;),
  Slava Razbash [aut],
  Earo Wang [aut] (ORCID: &lt;https://orcid.org/0000-0001-6448-5260&gt;),
  Farah Yasmeen [aut] (ORCID: &lt;https://orcid.org/0000-0002-1479-5401&gt;),
  Federico Garza [ctb],
  Daniele Girolimetto [ctb],
  Ross Ihaka [ctb, cph],
  R Core Team [ctb, cph],
  Daniel Reid [ctb],
  David Shaub [ctb],
  Yuan Tang [ctb] (ORCID: &lt;https://orcid.org/0000-0001-5243-233X&gt;),
  Xiaoqian Wang [ctb],
  Zhenyu Zhou [ctb]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2026-03-18</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=forecast</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.forecast</dc:identifier>
</oai_dc:dc>