ARIMA

The ARIMA model and its supported methods.

ARIMA()

Estimate an ARIMA model

forecast(<ARIMA>)

Forecast a model from the fable package

refit(<ARIMA>)

Refit an ARIMA model

interpolate(<ARIMA>)

Interpolate missing values from a fable model

fitted(<ARIMA>)

Extract fitted values from a fable model

residuals(<ARIMA>)

Extract residuals values from a fable model

ETS

Exponential smoothing state space models.

ETS()

Exponential smoothing state space model

forecast(<ETS>)

Forecast a model from the fable package

refit(<ETS>)

Refit an ETS model

generate(<ETS>)

Generate new data from a fable model

fitted(<ETS>)

Extract fitted values from a fable model

residuals(<ETS>)

Extract residuals values from a fable model

TSLM

Time series linear models.

TSLM()

Fit a linear model with time series components

forecast(<TSLM>)

Forecast a model from the fable package

refit(<TSLM>)

Refit a TSLM

generate(<TSLM>)

Generate new data from a fable model

interpolate(<TSLM>)

Interpolate missing values from a fable model

fitted(<TSLM>)

Extract fitted values from a fable model

residuals(<TSLM>)

Extract residuals values from a fable model

Simple forecasting methods

A collection of simple forecasting methods that are commonly used as benchmarks.

MEAN()

Mean models

RW() NAIVE() SNAIVE()

Random walk models

forecast(<model_mean>)

Forecast a model from the fable package

forecast(<RW>)

Forecast a model from the fable package

generate(<model_mean>)

Generate new data from a fable model

generate(<RW>)

Generate new data from a fable model

fitted(<model_mean>)

Extract fitted values from a fable model

fitted(<RW>)

Extract fitted values from a fable model

residuals(<model_mean>)

Extract residuals values from a fable model

residuals(<RW>)

Extract residuals values from a fable model

Neural network autoregression

Feed-forward neural networks with a single hidden layer and lagged inputs for forecasting univariate time series.

NNETAR()

Neural Network Time Series Forecasts

forecast(<NNETAR>)

Forecast a model from the fable package

generate(<NNETAR>)

Generate new data from a fable model

fitted(<NNETAR>)

Extract fitted values from a fable model

residuals(<NNETAR>)

Extract residuals values from a fable model

Vector autoregression

Estimates a VAR(p) model with support for exogenous regressors.

VAR()

Estimate a VAR model

forecast(<VAR>)

Forecast a model from the fable package

fitted(<VAR>)

Extract fitted values from a fable model

residuals(<VAR>)

Extract residuals values from a fable model