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 package, which implements many of the same models but in a tidyverse framework.
Installation
You can install the stable version from CRAN.
install.packages("forecast", dependencies = TRUE)
You can install the development version from Github
# install.packages("pak") pak::pak("robjhyndman/forecast")
Usage
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 = -0.4, d = 0.3)$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.