/forecast

Forecasting Functions for Time Series and Linear Models

Primary LanguageR

forecast

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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("remotes")
remotes::install_github("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=-.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

License

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