forecast
Forecasting Functions for Time Series and Linear Models
Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.
forecast 
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.