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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.
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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.