Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.
Version: | 8.23.0 |
Depends: | R (≥ 3.5.0) |
Imports: | colorspace, fracdiff, generics (≥ 0.1.2), ggplot2 (≥ 2.2.1), graphics, lmtest, magrittr, nnet, parallel, Rcpp (≥ 0.11.0), stats, timeDate, tseries, urca, withr, zoo |
LinkingTo: | Rcpp (≥ 0.11.0), RcppArmadillo (≥ 0.2.35) |
Suggests: | forecTheta, knitr, methods, rmarkdown, rticles, scales, seasonal, testthat (≥ 3.0.0), uroot |
Published: | 2024-06-20 |
DOI: | 10.32614/CRAN.package.forecast |
Author: | Rob Hyndman [aut, cre, cph], George Athanasopoulos [aut], Christoph Bergmeir [aut], Gabriel Caceres [aut], Leanne Chhay [aut], Kirill Kuroptev [aut], Mitchell O'Hara-Wild [aut], Fotios Petropoulos [aut], Slava Razbash [aut], Earo Wang [aut], Farah Yasmeen [aut], Federico Garza [ctb], Daniele Girolimetto [ctb], Ross Ihaka [ctb, cph], R Core Team [ctb, cph], Daniel Reid [ctb], David Shaub [ctb], Yuan Tang [ctb], Xiaoqian Wang [ctb], Zhenyu Zhou [ctb] |
Maintainer: | Rob Hyndman <Rob.Hyndman at monash.edu> |
BugReports: | https://github.com/robjhyndman/forecast/issues |
License: | GPL-3 |
URL: | https://pkg.robjhyndman.com/forecast/, https://github.com/robjhyndman/forecast |
NeedsCompilation: | yes |
Citation: | forecast citation info |
Materials: | README NEWS |
In views: | Econometrics, Environmetrics, Finance, MissingData, TimeSeries |
CRAN checks: | forecast results |
Reference manual: | forecast.pdf |
Vignettes: |
Automatic Time Series Forecasting: the forecast Package for R (Hyndman & Khandakar, JSS 2008) |
Package source: | forecast_8.23.0.tar.gz |
Windows binaries: | r-devel: forecast_8.23.0.zip, r-release: forecast_8.23.0.zip, r-oldrel: forecast_8.23.0.zip |
macOS binaries: | r-release (arm64): forecast_8.23.0.tgz, r-oldrel (arm64): forecast_8.23.0.tgz, r-release (x86_64): forecast_8.23.0.tgz, r-oldrel (x86_64): forecast_8.23.0.tgz |
Old sources: | forecast archive |
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