# Forecasting Functions for Time Series and Linear Models

## Documentation for package ‘forecast’ version 7.3

- DESCRIPTION file.

## Help Pages

A B C D E F G H I L M N P R S T W

## -- A --

accuracy | Accuracy measures for forecast model
Acf | (Partial) Autocorrelation and Cross-Correlation Function Estimation
arfima | Fit a fractionally differenced ARFIMA model
Arima | Fit ARIMA model to univariate time series
arima.errors | ARIMA errors
arimaorder | Return the order of an ARIMA or ARFIMA model
auto.arima | Fit best ARIMA model to univariate time series
autoplot.acf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation
autoplot.Arima | Plot characteristic roots from ARIMA model
autoplot.decomposed.ts | ggplot of a decomposed time series object
autoplot.ets | Plot components from ETS model
autoplot.forecast | Forecast plot
autoplot.mforecast | Multivariate forecast plot
autoplot.mpacf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation
autoplot.mts | Automatically create a ggplot for time series objects
autoplot.splineforecast | Forecast plot
autoplot.stl | ggplot STL object
autoplot.ts | Automatically create a ggplot for time series objects

## -- B --

bats | BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
best.arima | Fit best ARIMA model to univariate time series
bizdays | Number of trading days in each season
BoxCox | Box Cox Transformation
BoxCox.lambda | Automatic selection of Box Cox transformation parameter

## -- C --

Ccf | (Partial) Autocorrelation and Cross-Correlation Function Estimation
croston | Forecasts for intermittent demand using Croston's method
CV | Cross-validation statistic

## -- D --

dm.test | Diebold-Mariano test for predictive accuracy
dshw | Double-Seasonal Holt-Winters Forecasting

## -- E --

easter | Easter holidays in each season
ets | Exponential smoothing state space model

## -- F --

findfrequency | Find dominant frequency of a time series
fitted.Arima | h-step in-sample forecasts using ARIMA models
fitted.bats | h-step in-sample forecasts using bats models
fitted.ets | h-step in-sample forecasts using ets models
fitted.nnetar | h-step in-sample forecasts using nnetar models
fitted.tbats | h-step in-sample forecasts using tbats models
forecast | Forecasting time series
forecast.ar | Forecasting using ARIMA or ARFIMA models
forecast.Arima | Forecasting using ARIMA or ARFIMA models
forecast.bats | Forecasting using BATS and TBATS models
forecast.default | Forecasting time series
forecast.ets | Forecasting using ETS models
forecast.fracdiff | Forecasting using ARIMA or ARFIMA models
forecast.HoltWinters | Forecasting using Holt-Winters objects
forecast.lm | Forecast a linear model with possible time series components
forecast.mlm | Forecast a multiple linear model with possible time series components
forecast.mts | Forecasting time series
forecast.nnetar | Forecasting using neural network models
forecast.stl | Forecasting using stl objects
forecast.stlm | Forecasting using stl objects
forecast.StructTS | Forecasting using Structural Time Series models
forecast.tbats | Forecasting using BATS and TBATS models
forecast.ts | Forecasting time series
fortify.forecast | Fortify a forecast object to data.frame for ggplot
fortify.ts | Automatically create a ggplot for time series objects
fourier | Seasonal dummy variables
fourierf | Seasonal dummy variables

## -- G --

gas | Australian monthly gas production
GeomForecast | Forecast plot
geom_forecast | Forecast plot
getResponse | Get response variable from time series model.
ggAcf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation
ggCcf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation
gglagchull | Time series lag ggplots
gglagplot | Time series lag ggplots
ggmonthplot | Create a seasonal subseries ggplot
ggPacf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation
ggseasonplot | Seasonal plot
ggtaperedacf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation
ggtaperedpacf | ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation
ggtsdisplay | Time series display
gold | Daily morning gold prices

## -- H --

holt | Exponential smoothing forecasts
hw | Exponential smoothing forecasts

## -- I --

InvBoxCox | Box Cox Transformation
is.acf | Is an object a particular model type?
is.Arima | Is an object a particular model type?
is.bats | Is an object a particular model type?
is.constant | Is an object constant?
is.ets | Is an object a particular model type?
is.forecast | Is an object a particular forecast type?
is.mforecast | Is an object a particular forecast type?
is.nnetar | Is an object a particular model type?
is.nnetarmodels | Is an object a particular model type?
is.splineforecast | Is an object a particular forecast type?
is.stlm | Is an object a particular model type?

## -- L --

logLik.ets | Log-Likelihood of an ets object

## -- M --

ma | Moving-average smoothing
meanf | Mean Forecast
mforecast | Forecasting time series
monthdays | Number of days in each season
msts | Multi-Seasonal Time Series

## -- N --

na.interp | Interpolate missing values in a time series
naive | Naive and Random Walk Forecasts
ndiffs | Number of differences required for a stationary series
nnetar | Neural Network Time Series Forecasts
nsdiffs | Number of differences required for a stationary series

## -- P --

Pacf | (Partial) Autocorrelation and Cross-Correlation Function Estimation
plot.ar | Plot characteristic roots from ARIMA model
plot.Arima | Plot characteristic roots from ARIMA model
plot.bats | Plot components from BATS model
plot.ets | Plot components from ETS model
plot.forecast | Forecast plot
plot.mforecast | Multivariate forecast plot
plot.splineforecast | Forecast plot
plot.tbats | Plot components from BATS model
print.forecast | Forecasting time series
print.mforecast | Forecasting time series

## -- R --

rwf | Naive and Random Walk Forecasts

## -- S --

seasadj | Seasonal adjustment
seasonaldummy | Seasonal dummy variables
seasonaldummyf | Seasonal dummy variables
seasonplot | Seasonal plot
ses | Exponential smoothing forecasts
simulate.ar | Simulation from a time series model
simulate.Arima | Simulation from a time series model
simulate.ets | Simulation from a time series model
simulate.fracdiff | Simulation from a time series model
simulate.nnetar | Simulation from a time series model
sindexf | Forecast seasonal index
snaive | Naive and Random Walk Forecasts
splinef | Cubic Spline Forecast
StatForecast | Forecast plot
stl | Forecasting using stl objects
stlf | Forecasting using stl objects
stlm | Forecasting using stl objects
subset.ts | Subsetting a time series
summary.forecast | Forecasting time series
summary.mforecast | Forecasting time series

## -- T --

taperedacf | (Partial) Autocorrelation and Cross-Correlation Function Estimation
taperedpacf | (Partial) Autocorrelation and Cross-Correlation Function Estimation
taylor | Half-hourly electricity demand
tbats | TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
tbats.components | Extract components of a TBATS model
thetaf | Theta method forecast
tsclean | Identify and replace outliers and missing values in a time series
tsdisplay | Time series display
tslm | Fit a linear model with time series components
tsoutliers | Identify and replace outliers in a time series

## -- W --

wineind | Australian total wine sales
woolyrnq | Quarterly production of woollen yarn in Australia