Forecast a model from the fable package

Produces forecasts from a trained model.

# S3 method for NNETAR
forecast(
  object,
  new_data,
  specials = NULL,
  simulate = TRUE,
  bootstrap = FALSE,
  times = 5000,
  ...
)

Arguments

object

A model for which forecasts are required.

new_data

A tsibble containing the time points and exogenous regressors to produce forecasts for.

specials

(passed by fabletools::forecast.mdl_df()).

simulate

If TRUE, forecast distributions are produced by sampling from a normal distribution. Without simulation, forecast uncertainty cannot be estimated for this model and instead a degenerate distribution with the forecast mean will be produced.

bootstrap

If TRUE, forecast distributions are produced by sampling from the model's training residuals.

times

The number of sample paths to use in producing the forecast distribution. Setting simulate = FALSE or times = 0 will produce degenerate forecast distributions of the forecast mean.

...

Other arguments passed to methods

Value

A list of forecasts.

Examples

as_tsibble(airmiles) %>%
  model(nn = NNETAR(box_cox(value, 0.15))) %>%
  forecast(times = 10)
#> # A fable: 2 x 4 [1Y]
#> # Key:     .model [1]
#>   .model index      value  .mean
#>   <chr>  <dbl>     <dist>  <dbl>
#> 1 nn      1961 sample[10] 31085.
#> 2 nn      1962 sample[10] 33936.