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of Contents"],"sub_categories":["Time series"],"readme":"forecast \u003cimg src=\"man/figures/logo.png\" align=\"right\" /\u003e\n======================\n\n[![R-CMD-check](https://github.com/robjhyndman/forecast/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/robjhyndman/forecast/actions/workflows/R-CMD-check.yaml)\n[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/forecast)](https://cran.r-project.org/package=forecast)\n[![Downloads](https://cranlogs.r-pkg.org/badges/forecast)](https://cran.r-project.org/package=forecast)\n[![Licence](https://img.shields.io/badge/licence-GPL--3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0.en.html)\n\nThe R package *forecast* provides methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.\n\nA complementary forecasting package is the [fable](http://fable.tidyverts.org/) package, which implements many of the same models but in a tidyverse framework.\n\n## Installation\nYou can install the **stable** version from\n[CRAN](https://cran.r-project.org/package=forecast).\n\n```s\ninstall.packages(\"forecast\", dependencies = TRUE)\n```\n\nYou can install the **development** version from\n[Github](https://github.com/robjhyndman/forecast)\n\n```s\n# install.packages(\"remotes\")\nremotes::install_github(\"robjhyndman/forecast\")\n```\n\n## Usage\n\n```s\nlibrary(forecast)\nlibrary(ggplot2)\n\n# ETS forecasts\nUSAccDeaths |\u003e\n  ets() |\u003e\n  forecast() |\u003e\n  autoplot()\n\n# Automatic ARIMA forecasts\nWWWusage |\u003e\n  auto.arima() |\u003e\n  forecast(h=20) |\u003e\n  autoplot()\n\n# ARFIMA forecasts\nlibrary(fracdiff)\nx \u003c- fracdiff.sim( 100, ma=-.4, d=.3)$series\narfima(x) |\u003e\n  forecast(h=30) |\u003e\n  autoplot()\n\n# Forecasting with STL\nUSAccDeaths |\u003e\n  stlm(modelfunction=ar) |\u003e\n  forecast(h=36) |\u003e\n  autoplot()\n\nAirPassengers |\u003e\n  stlf(lambda=0) |\u003e\n  autoplot()\n\nUSAccDeaths |\u003e\n  stl(s.window='periodic') |\u003e\n  forecast() |\u003e\n  autoplot()\n\n# TBATS forecasts\nUSAccDeaths |\u003e\n  tbats() |\u003e\n  forecast() |\u003e\n  autoplot()\n\ntaylor |\u003e\n  tbats() |\u003e\n  forecast() |\u003e\n  autoplot()\n```\n\n## For more information\n\n  * Get started in forecasting with the online textbook at http://OTexts.org/fpp2/\n  * Read the Hyndsight blog at https://robjhyndman.com/hyndsight/\n  * Ask forecasting questions on http://stats.stackexchange.com/tags/forecasting\n  * Ask R questions on http://stackoverflow.com/tags/forecasting+r\n  * Join the International Institute of Forecasters: http://forecasters.org/\n\n## License\n\nThis package is free and open source software, licensed under GPL-3.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frobjhyndman%2Fforecast","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frobjhyndman%2Fforecast","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frobjhyndman%2Fforecast/lists"}