generate.ARIMA: Generate new data from a fable model

In fable: Forecasting Models for Tidy Time Series

Generate new data from a fable model

Description

Simulates future paths from a dataset using a fitted model. Innovations are sampled by the model's assumed error distribution. If bootstrap is TRUE, innovations will be sampled from the model's residuals. If new_data contains the .innov column, those values will be treated as innovations.

Usage

## S3 method for class 'ARIMA'
generate(x, new_data, specials, bootstrap = FALSE, ...)

Arguments

x	A fitted model.
new_data	A tsibble containing the time points and exogenous regressors to produce forecasts for.
specials	(passed by fabletools::forecast.mdl_df()).
bootstrap	If TRUE, then forecast distributions are computed using simulation with resampled errors.
...	Other arguments passed to methods

See Also

fabletools::generate.mdl_df

Examples

fable_fit <- as_tsibble(USAccDeaths) %>%
  model(model = ARIMA(value ~ 0 + pdq(0,1,1) + PDQ(0,1,1)))
fable_fit %>% generate(times = 10)

fable documentation built on April 12, 2025, 1:51 a.m.