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Forecasting Functions for Time Series and Linear Models
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robjhyndman/forecast
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The R packageforecast 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 thefable package, which implements many of the same models but in a tidyverse framework.
You can install thestable version fromCRAN.
install.packages("forecast", dependencies = TRUE)
You can install thedevelopment version fromGithub
# install.packages("remotes")remotes::install_github("robjhyndman/forecast")
library(forecast)library(ggplot2)# ETS forecastsUSAccDeaths |> ets() |> forecast() |> autoplot()# Automatic ARIMA forecastsWWWusage |> auto.arima() |> forecast(h=20) |> autoplot()# ARFIMA forecastslibrary(fracdiff)x <- fracdiff.sim(100, ma=-.4, d=.3)$seriesarfima(x) |> forecast(h=30) |> autoplot()# Forecasting with STLUSAccDeaths |> stlm(modelfunction=ar) |> forecast(h=36) |> autoplot()AirPassengers |> stlf(lambda=0) |> autoplot()USAccDeaths |> stl(s.window='periodic') |> forecast() |> autoplot()# TBATS forecastsUSAccDeaths |> tbats() |> forecast() |> autoplot()taylor |> tbats() |> forecast() |> autoplot()
- Get started in forecasting with the online textbook athttp://OTexts.org/fpp2/
- Read the Hyndsight blog athttps://robjhyndman.com/hyndsight/
- Ask forecasting questions onhttp://stats.stackexchange.com/tags/forecasting
- Ask R questions onhttp://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.
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