Forecasting Functions for Time Series and Linear Models

---

Documentation for package ‘forecast’ version 8.22.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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

forecast-package

forecast: Forecasting Functions for Time Series and Linear Models

-- A --

accuracy.default	Accuracy measures for a 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	Errors from a regression model with ARIMA errors
arimaorder	Return the order of an ARIMA or ARFIMA model
as.character.Arima	Fit ARIMA model to univariate time series
as.character.bats	BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
as.character.ets	Exponential smoothing state space model
as.character.tbats	TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
as.data.frame.forecast	Forecasting time series
as.data.frame.mforecast	Forecasting time series
as.ts.forecast	Forecasting time series
auto.arima	Fit best ARIMA model to univariate time series
autolayer	Create a ggplot layer appropriate to a particular data type
autolayer.forecast	Forecast plot
autolayer.mforecast	Multivariate forecast plot
autolayer.msts	Automatically create a ggplot for time series objects
autolayer.mts	Automatically create a ggplot for time series objects
autolayer.ts	Automatically create a ggplot for time series objects
autoplot.acf	ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation and Plotting
autoplot.ar	Plot characteristic roots from ARIMA model
autoplot.Arima	Plot characteristic roots from ARIMA model
autoplot.bats	Plot components from BATS model
autoplot.decomposed.ts	Plot time series decomposition components using ggplot
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 and Plotting
autoplot.mstl	Plot time series decomposition components using ggplot
autoplot.msts	Automatically create a ggplot for time series objects
autoplot.mts	Automatically create a ggplot for time series objects
autoplot.seas	Plot time series decomposition components using ggplot
autoplot.splineforecast	Forecast plot
autoplot.stl	Plot time series decomposition components using ggplot
autoplot.StructTS	Plot time series decomposition components using ggplot
autoplot.tbats	Plot components from BATS model
autoplot.ts	Automatically create a ggplot for time series objects

-- B --

baggedETS	Forecasting using a bagged model
baggedModel	Forecasting using a bagged model
bats	BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
bizdays	Number of trading days in each season
bld.mbb.bootstrap	Box-Cox and Loess-based decomposition bootstrap.
BoxCox	Box Cox Transformation
BoxCox.lambda	Automatic selection of Box Cox transformation parameter

-- C --

Ccf	(Partial) Autocorrelation and Cross-Correlation Function Estimation
checkresiduals	Check that residuals from a time series model look like white noise
coef.ets	Exponential smoothing state space model
croston	Forecasts for intermittent demand using Croston's method
CV	Cross-validation statistic
CVar	k-fold Cross-Validation applied to an autoregressive model

-- 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.ar	h-step in-sample forecasts for time series models.
fitted.ARFIMA	h-step in-sample forecasts for time series models.
fitted.Arima	h-step in-sample forecasts for time series models.
fitted.bats	h-step in-sample forecasts for time series models.
fitted.ets	h-step in-sample forecasts for time series models.
fitted.forecast_ARIMA	h-step in-sample forecasts for time series models.
fitted.modelAR	h-step in-sample forecasts for time series models.
fitted.nnetar	h-step in-sample forecasts for time series models.
fitted.tbats	h-step in-sample forecasts for time series models.
forecast.ar	Forecasting using ARIMA or ARFIMA models
forecast.Arima	Forecasting using ARIMA or ARFIMA models
forecast.baggedModel	Forecasting using a bagged model
forecast.bats	Forecasting using BATS and TBATS models
forecast.default	Forecasting time series
forecast.ets	Forecasting using ETS models
forecast.forecast_ARIMA	Forecasting using ARIMA or ARFIMA 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.modelAR	Forecasting using user-defined model
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.ts	Automatically create a ggplot for time series objects
fourier	Fourier terms for modelling seasonality
fourierf	Fourier terms for modelling seasonality

-- G --

gas	Australian monthly gas production
GeomForecast	Forecast plot
geom_forecast	Forecast plot
getResponse	Get response variable from time series model.
getResponse.ar	Get response variable from time series model.
getResponse.Arima	Get response variable from time series model.
getResponse.baggedModel	Get response variable from time series model.
getResponse.bats	Get response variable from time series model.
getResponse.default	Get response variable from time series model.
getResponse.fracdiff	Get response variable from time series model.
getResponse.lm	Get response variable from time series model.
getResponse.mforecast	Get response variable from time series model.
getResponse.tbats	Get response variable from time series model.
ggAcf	ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation and Plotting
ggCcf	ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation and Plotting
gghistogram	Histogram with optional normal and kernel density functions
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 and Plotting
ggseasonplot	Seasonal plot
ggsubseriesplot	Create a seasonal subseries ggplot
ggtaperedacf	ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation and Plotting
ggtaperedpacf	ggplot (Partial) Autocorrelation and Cross-Correlation Function Estimation and Plotting
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.baggedModel	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.modelAR	Is an object a particular model 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?

-- M --

ma	Moving-average smoothing
meanf	Mean Forecast
mforecast	Forecasting time series
modelAR	Time Series Forecasts with a user-defined model
modeldf	Compute model degrees of freedom
monthdays	Number of days in each season
mstl	Multiple seasonal decomposition
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 seasonally stationary series

-- O --

ocsb.test

Osborn, Chui, Smith, and Birchenhall Test for Seasonal Unit Roots

-- 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.ARIMA	Fit ARIMA model to univariate time series
print.baggedModel	Forecasting using a bagged model
print.bats	BATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)
print.CVar	k-fold Cross-Validation applied to an autoregressive model
print.ets	Exponential smoothing state space model
print.forecast	Forecasting time series
print.mforecast	Forecasting time series
print.modelAR	Time Series Forecasts with a user-defined model
print.msts	Multi-Seasonal Time Series
print.naive	Naive and Random Walk Forecasts
print.nnetar	Neural Network Time Series Forecasts
print.nnetarmodels	Neural Network Time Series Forecasts
print.OCSBtest	Osborn, Chui, Smith, and Birchenhall Test for Seasonal Unit Roots
print.tbats	TBATS model (Exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components)

-- R --

remainder	Extract components from a time series decomposition
residuals.ar	Residuals for various time series models
residuals.ARFIMA	Residuals for various time series models
residuals.Arima	Residuals for various time series models
residuals.bats	Residuals for various time series models
residuals.ets	Residuals for various time series models
residuals.forecast	Residuals for various time series models
residuals.forecast_ARIMA	Residuals for various time series models
residuals.nnetar	Residuals for various time series models
residuals.stlm	Residuals for various time series models
residuals.tbats	Residuals for various time series models
residuals.tslm	Residuals for various time series models
rwf	Naive and Random Walk Forecasts

-- S --

seasadj	Seasonal adjustment
seasadj.decomposed.ts	Seasonal adjustment
seasadj.mstl	Seasonal adjustment
seasadj.seas	Seasonal adjustment
seasadj.stl	Seasonal adjustment
seasadj.tbats	Seasonal adjustment
seasonal	Extract components from a time series decomposition
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.lagwalk	Simulation from a time series model
simulate.modelAR	Simulation from a time series model
simulate.nnetar	Simulation from a time series model
simulate.tbats	Simulation from a time series model
sindexf	Forecast seasonal index
snaive	Naive and Random Walk Forecasts
splinef	Cubic Spline Forecast
StatForecast	Forecast plot
stlf	Forecasting using stl objects
stlm	Forecasting using stl objects
subset.msts	Subsetting a time series
subset.ts	Subsetting a time series
summary.Arima	Fit ARIMA model to univariate time series
summary.ets	Exponential smoothing state space model
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
trendcycle	Extract components from a time series decomposition
tsclean	Identify and replace outliers and missing values in a time series
tsCV	Time series cross-validation
tsdiag.ets	Exponential smoothing state space model
tsdisplay	Time series display
tslm	Fit a linear model with time series components
tsoutliers	Identify and replace outliers in a time series

-- W --

window.msts	Multi-Seasonal Time Series
wineind	Australian total wine sales
woolyrnq	Quarterly production of woollen yarn in Australia

-- misc --

`[.msts`

Multi-Seasonal Time Series