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.
install.packages("forecast", dependencies = TRUE)You can install the development version from Github
# install.packages("pak")
pak::pak("robjhyndman/forecast")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()- 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/
This package is free and open source software, licensed under GPL-3.