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.
You can install the stable version from CRAN.
("forecast", dependencies = TRUE) install.packages
You can install the development version from Github
# install.packages("remotes")
remotes::install_github("robjhyndman/forecast")
(forecast)
library(ggplot2)
library
# ETS forecasts
|>
USAccDeaths () |>
ets() |>
forecast()
autoplot
# Automatic ARIMA forecasts
|>
WWWusage () |>
auto.arima(h=20) |>
forecast()
autoplot
# ARFIMA forecasts
(fracdiff)
library<- fracdiff.sim( 100, ma=-.4, d=.3)$series
x (x) |>
arfima(h=30) |>
forecast()
autoplot
# Forecasting with STL
|>
USAccDeaths (modelfunction=ar) |>
stlm(h=36) |>
forecast()
autoplot
|>
AirPassengers (lambda=0) |>
stlf()
autoplot
|>
USAccDeaths (s.window='periodic') |>
stl() |>
forecast()
autoplot
# TBATS forecasts
|>
USAccDeaths () |>
tbats() |>
forecast()
autoplot
|>
taylor () |>
tbats() |>
forecast() autoplot
This package is free and open source software, licensed under GPL-3.