Forecasting Functions for Time Series and Linear Models


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Documentation for package ‘forecast’ version 8.23.0

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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