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 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 from a fable model

components(<ETS>)

Extract estimated states from an ETS 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 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

refit(<model_mean>)

Refit a MEAN model

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 from a fable model

residuals(<RW>)

Extract residuals 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

refit(<NNETAR>)

Refit a NNETAR model

generate(<NNETAR>)

Generate new data from a fable model

fitted(<NNETAR>)

Extract fitted values from a fable model

residuals(<NNETAR>)

Extract residuals from a fable model

Croston's method

Croston’s (1972) method for intermittent demand forecasting

CROSTON()

Croston's method

forecast(<croston>)

Forecast a model from the fable package

fitted(<croston>)

Extract fitted values from a fable model

residuals(<croston>)

Extract residuals from a fable model

Theta method

The Theta method of Assimakopoulos and Nikolopoulos (2000)

THETA()

Theta method

Autoregression

Autoregressive time series models

AR()

Estimate a AR model

forecast(<AR>)

Forecast a model from the fable package

refit(<AR>)

Refit an AR model

generate(<AR>)

Generate new data from a fable model

fitted(<AR>)

Extract fitted values from a fable model

residuals(<AR>)

Extract residuals 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 from a fable model