Forecast a model from the fable package

Produces forecasts from a trained model.

# S3 method for class 'model_mean'
forecast(
  object,
  new_data,
  specials = NULL,
  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()).

bootstrap

If TRUE, then forecast distributions are computed using simulation with resampled errors.

times

The number of sample paths to use in estimating the forecast distribution when bootstrap = TRUE.

...

Other arguments passed to methods

Value

A list of forecasts.

Examples

library(tsibbledata)
vic_elec %>%
  model(avg = MEAN(Demand)) %>%
  forecast()
#> # A fable: 4 x 4 [30m] <Australia/Melbourne>
#> # Key:     .model [1]
#>   .model Time               
#>   <chr>  <dttm>             
#> 1 avg    2015-01-01 00:00:00
#> 2 avg    2015-01-01 00:30:00
#> 3 avg    2015-01-01 01:00:00
#> 4 avg    2015-01-01 01:30:00
#> # ℹ 2 more variables: Demand <dist>, .mean <dbl>