README.md
In a1967fa/f-cast: Forecasting Functions for Time Series and Linear Models

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.

You can install the stable version from CRAN.

install.packages('forecast', dependencies = TRUE)

You can install the development version from Github

# install.packages("devtools")
devtools::install_github("robjhyndman/forecast")

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