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.
You can install the development version from Github
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()
This package is free and open source software, licensed under GPL-3.