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https://github.com/robjhyndman/forecast

Forecasting Functions for Time Series and Linear Models
https://github.com/robjhyndman/forecast

cran forecast forecasting r

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Forecasting Functions for Time Series and Linear Models

Host: GitHub
URL: https://github.com/robjhyndman/forecast
Owner: robjhyndman
Created: 2012-04-22T23:19:09.000Z (over 12 years ago)
Default Branch: master
Last Pushed: 2024-08-30T03:02:00.000Z (4 months ago)
Last Synced: 2024-12-31T02:06:28.155Z (12 days ago)
Topics: cran, forecast, forecasting, r
Language: R
Homepage: http://pkg.robjhyndman.com/forecast
Size: 211 MB
Stars: 1,129
Watchers: 85
Forks: 341
Open Issues: 12
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md

Awesome Lists containing this project

jimsghstars - robjhyndman/forecast - Forecasting Functions for Time Series and Linear Models (R)

README

        forecast 

======================

[![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)

[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/forecast)](https://cran.r-project.org/package=forecast)

[![Downloads](https://cranlogs.r-pkg.org/badges/forecast)](https://cran.r-project.org/package=forecast)

[![Licence](https://img.shields.io/badge/licence-GPL--3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0.en.html)

The 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.

A complementary forecasting package is the [fable](http://fable.tidyverts.org/) package, which implements many of the same models but in a tidyverse framework.

## Installation

You can install the **stable** version from

[CRAN](https://cran.r-project.org/package=forecast).

```s

install.packages("forecast", dependencies = TRUE)

```

You can install the **development** version from

[Github](https://github.com/robjhyndman/forecast)

```s

# install.packages("remotes")

remotes::install_github("robjhyndman/forecast")

```

## Usage

```s

library(forecast)

library(ggplot2)

# ETS forecasts

USAccDeaths |>

  ets() |>

  forecast() |>

  autoplot()

# Automatic ARIMA forecasts

WWWusage |>

  auto.arima() |>

  forecast(h=20) |>

  autoplot()

# ARFIMA forecasts

library(fracdiff)

x <- fracdiff.sim( 100, ma=-.4, d=.3)$series

arfima(x) |>

  forecast(h=30) |>

  autoplot()

# Forecasting with STL

USAccDeaths |>

  stlm(modelfunction=ar) |>

  forecast(h=36) |>

  autoplot()

AirPassengers |>

  stlf(lambda=0) |>

  autoplot()

USAccDeaths |>

  stl(s.window='periodic') |>

  forecast() |>

  autoplot()

# TBATS forecasts

USAccDeaths |>

  tbats() |>

  forecast() |>

  autoplot()

taylor |>

  tbats() |>

  forecast() |>

  autoplot()

```

## For more information

  * Get started in forecasting with the online textbook at http://OTexts.org/fpp2/

  * Read the Hyndsight blog at https://robjhyndman.com/hyndsight/

  * Ask forecasting questions on http://stats.stackexchange.com/tags/forecasting

  * Ask R questions on http://stackoverflow.com/tags/forecasting+r

  * Join the International Institute of Forecasters: http://forecasters.org/

## License

This package is free and open source software, licensed under GPL-3.